Dynamic Cheatsheet epistemic report
Type: agentic-system-analyses/types/agentic-system-epistemic-report.md
Source-and-claim boundary
The question is whether the shipped inference-memory loop turns solutions into warranted reusable content, and what gives that content force in later solving. Scope, dependencies and exclusions are those of the boundary; evidence identities are in its Source register. This member adds direct source inspection within SRC-1, not another source or revision. Implementation evidence establishes wiring, not successful model judgment. No target execution was performed.
The public memory and learning claim is RT-CLM-adaptive-memory. More specific warrant and performance claims are EPI-CLM-verified-solutions and EPI-CLM-performance-gains. Instructions to verify are compared with the actual admission and score consumers, rather than treated as successful verification.
| Entry point or operation | Source path, SRC-1 | Coverage and records | Limit and conclusion prevented |
|---|---|---|---|
| CLI setup, prompt default, import, initialization and resume | run_benchmark.py |
Direct full read; RT-RTE-benchmark-cycle | Dataset/embedding payload integrity uninspected; no label-truth or vector-quality finding |
| Six approaches and repeated cumulative rounds | dynamic_cheatsheet/language_model.py |
Direct full read; RT-RTE-context-selection, RT-RTE-cumulative-update | No observed semantic compliance or capacity improvement |
| Answer, sheet and solution-evaluation extraction | dynamic_cheatsheet/utils/extractor.py |
Direct full read; EPI-RTE-sheet-admission, EPI-ABS-score-feedback | Standalone extract_solution is a string slicer, not a truth evaluator or a called admission gate |
| Cumulative and synthesis instructions; generator reliance | prompts/curator_prompt_for_dc_cumulative.txt, prompts/curator_prompt_for_dc_retrieval_synthesis.txt, prompts/generator_prompt.txt |
Direct full reads; EPI-RTE-curator-review, RT-BAP-reference-context | Requested tests, usage counts and references are not machine-checked assertions |
| Local and hosted execution | dynamic_cheatsheet/language_model.py, dynamic_cheatsheet/utils/execute_code.py, text_generation/simple_unified_client.py |
Direct wrapper read and adapter generate_from_messages; executor/provider internals of wrapper routes otherwise supplied by RT-RTE-local-execution, RT-RTE-provider-execution |
A calculation result does not validate encoding, premises or generalization; hosted tool progression uninspected |
| Four task-scoring families and auxiliary evaluators | dynamic_cheatsheet/utils/evaluation.py |
Direct full read; RT-RTE-score-answer, EPI-OBJ-score-result | Checkmate, soft match and programming-puzzle helpers not dispatched by the inspected CLI/notebook; no observed quality judgment |
| Interactive caller and post-hoc evaluator | ExampleUsage.ipynb, EvaluatingResults.ipynb |
Example caller supplied runtime finding; evaluator cell source directly read, outputs omitted; RT-RTE-benchmark-cycle, RT-RTE-score-answer | Saved notebook outputs not assessed; no observed benefit or authentic run attribution |
| Poetry checker and corpus/test operations | dynamic_cheatsheet/utils/sonnet_eval.py |
Direct interface/docstring read and function/call search; no CLI/notebook call found; standalone implementation otherwise unassessed | Its separate rhyme/syllable evaluator is not a memory-admission consumer; prevents a system-complete negative about all checking capabilities |
| Standalone chat/web-search/provider conveniences | text_generation/simple_unified_client.py |
Function inventory directly searched; ordinary wrapper dispatch directly inspected; remaining provider details supplied runtime findings | Standalone acquisition/chat APIs remain unassessed, not absent; no universal negative about external-evidence acquisition |
| Documentation and result corpus | README.md, results/ |
README directly read; EPI-CLM-performance-gains; historical payloads uninspected | No independently inspected observed run or causal comparison; performance attribution remains reported only |
The available but uninspected datasets, vectors, result payloads, poetry-checker internals and standalone adapter APIs are not access gaps. They bound conclusions rather than justify an assertion that the whole repository lacks evaluators. Remote model internals, current service behavior and the linked paper are outside the frozen evidence, as specified by the boundary. They prevent exact parameter-state, live compatibility and independently assessed experimental claims. None is needed to establish the inspected separation between sheet admission and benchmark scoring.
Epistemic-object inventory
| Object ID | Candidate truth-apt content or none | Claimed role | Evidence source ID and local anchor | Gap/limit |
|---|---|---|---|---|
| EPI-OBJ-cheatsheet | Strategies' applicability claims, examples, theorem statements and code behavior claims; policy advice need not be truth-apt | See record | SRC-1, dynamic_cheatsheet/language_model.py, curator prompts in record |
Mixed semantic content; actual generated claims not individuated in this source-only analysis |
| EPI-OBJ-generator-output | Proposed answers, explanations, code and embedded execution-result text | See record | SRC-1, dynamic_cheatsheet/language_model.py |
Model assertion, executed output and formal proof are different; transcript concatenation does not certify them |
| EPI-OBJ-score-result | Boolean assertion that extracted answer passes a task-specific program | See record | SRC-1, dynamic_cheatsheet/utils/evaluation.py, run_benchmark.py |
Does not assert the strategy or explanation is correct |
| EPI-OBJ-target | Imported expected answer or reference equation | See record | SRC-1, run_benchmark.py |
Dataset source warrant unknown; labels reach scorers, not curator input |
| RT-CMP-language-model | Not determinable at the level of individual propositions in weights | See record | SRC-1, dynamic_cheatsheet/language_model.py, README.md |
No source-owned weight update; remote parameter lineage and exact endpoint state uninspected |
| RT-OBJ-output-dict | None in keys/serialization themselves; text parts above carry content | See record | SRC-1, dynamic_cheatsheet/language_model.py, run_benchmark.py |
Stored envelopes do not constitute acceptance records |
| RT-RTE-context-selection | Retained prior question/output pairs contain candidate claims; numerical similarities carry ranking, not truth warrant | See record | SRC-1, dynamic_cheatsheet/language_model.py |
Precomputed vector provenance unresolved; old answers are not replaced by targets |
Authority-route ledger
The linked records own shared identity, progression, activation and evidence fields; see references below avoid redeclaring them. Architectural status and content/update classifications below are this overlay's assessments. Repeated citations split functions of a route, not its identity. No implemented force here is a claim of observed compliance.
Route ID: RT-RTE-benchmark-cycle
Route function: content transformation
Architectural status: implemented
Object/candidate ID: EPI-OBJ-target, EPI-OBJ-cheatsheet
Content/update relation: truth-apt transformation: acquisition/import
Transition or check target: external problem/target loading and optional initial sheet or resumed rows.
Evaluator/condition and domain: file/dataset reads and argument consistency checks, not truth evaluation.
Activation and timing: see route; before subsequent question generation.
Possible or observed result: supplied text and target available; source warrant unknown, not upgraded by import.
Implemented force: inputs supplied to distinct consumers.
Epistemic authority and scope: no new source-truth license.
Operational authority: initialization or resume can determine later reference text without per-entry approval.
Behavioral-authority path: generator/curator via sheet user-message content, advisory across later queries; scorer via target argument, enforcing Boolean computation only.
Evidence source ID and local anchor: SRC-1, run_benchmark.py; see route.
Claim IDs or none: RT-CLM-adaptive-memory.
Mismatch marker or none: none.
Gap/limit: import fidelity is inspectable at the field level, but provenance and truth of imported content remain unknown.
Route ID: RT-RTE-cumulative-update
Route function: content transformation
Architectural status: implemented
Object/candidate ID: EPI-OBJ-generator-output, EPI-OBJ-cheatsheet
Content/update relation: truth-apt transformation: indeterminate
Transition or check target: generator produces answer; curator proposes a replacement sheet after the answer.
Evaluator/condition and domain: see route; same provider-backed model, guided by supplied templates.
Activation and timing: cumulative rounds; one hybrid update. Generator is before curator.
Possible or observed result: candidate answers and reusable text requested; actual semantic relation unobserved.
Implemented force: returned/extracted text, not verified derivation.
Epistemic authority and scope: source code alone cannot classify outputs as mere compression, entailed derivation or ampliative conjecture. The prompt permits generalization, but permission is not an emitted non-entailing proposition.
Operational authority: admitted sheet can become subsequent reference text.
Behavioral-authority path: see RT-BAP-reference-context.
Evidence source ID and local anchor: SRC-1, dynamic_cheatsheet/language_model.py, prompts/curator_prompt_for_dc_cumulative.txt; see route.
Claim IDs or none: RT-CLM-adaptive-memory, EPI-CLM-verified-solutions.
Mismatch marker or none: requested verified/generalizable output is not itself verified/generalizable output.
Gap/limit: actual candidate contents and linked judgments needed to decide remaining semantic classifications; bare CLI defaults omit these curator instructions.
Route ID: EPI-RTE-curator-review
Route function: check/evidence production
Architectural status: implemented
Object/candidate ID: EPI-OBJ-generator-output
Content/update relation: no content change
Transition or check target: correctness and usefulness of current solution for future reference.
Evaluator/condition and domain: model judgment requested by cumulative prompt; no independent target is passed.
Activation and timing: see record; after answer, before extraction.
Possible or observed result: model may reject, correct, preserve or generalize content within proposed sheet; no structured judgment is inspected.
Implemented force: advisory instructions influence the proposal; no separately parsed pass/fail result.
Epistemic authority and scope: requested assessment, not evidence-consuming acceptance against an independently checked outcome.
Operational authority: curator chooses what text to include; Python does not enforce its reasoning.
Behavioral-authority path: curator via prompt, advisory on current proposal; proposal passes to extractor.
Evidence source ID and local anchor: SRC-1, prompts/curator_prompt_for_dc_cumulative.txt, dynamic_cheatsheet/language_model.py; see record.
Claim IDs or none: EPI-CLM-verified-solutions.
Mismatch marker or none: semantic validation delegated to model, not established by software admission.
Gap/limit: critique could occur in opaque model processing, but neither successful checking nor absence of formulated criticism follows from that opacity.
Route ID: EPI-RTE-sheet-admission
Route function: disposition/acceptance
Architectural status: implemented
Object/candidate ID: EPI-OBJ-cheatsheet
Content/update relation: truth-apt transformation: non-ampliative reshaping
Transition or check target: extract tagged replacement text; accept it operationally or use fallback.
Evaluator/condition and domain: opening tag/string splitting; formatting only.
Activation and timing: after cumulative/hybrid curator, or before retrieval-synthesis generator; see record.
Possible or observed result: extracted substring replaces sheet; no opening tag returns fallback. Missing closing tag still permits replacement.
Implemented force: enforcing selection of live text.
Epistemic authority and scope: no truth license from delimiters. This is operational admission, not epistemic acceptance.
Operational authority: arbitrary tagged text, including false claims, can reach later generator context before any independent check.
Behavioral-authority path: extractor to carried sheet/current synthesis, enforcing at write; generator via user prompt, advisory at later use.
Evidence source ID and local anchor: SRC-1, dynamic_cheatsheet/utils/extractor.py, dynamic_cheatsheet/language_model.py; see record's concrete trace.
Claim IDs or none: EPI-CLM-verified-solutions.
Mismatch marker or none: no correctness veto at this admission boundary.
Gap/limit: classification concerns substring extraction only, not semantic preservation by the preceding model call.
Route ID: RT-RTE-context-selection
Route function: operational admission/selection/consumption
Architectural status: implemented
Object/candidate ID: EPI-OBJ-generator-output, EPI-OBJ-cheatsheet
Content/update relation: truth-apt transformation: non-ampliative reshaping
Transition or check target: choose/format all prior pairs or cosine-top-k pairs; default empties reference context.
Evaluator/condition and domain: approach dispatch, cosine ranking, array indexing and string formatting; relevance heuristic, not truth test.
Activation and timing: see route; before generation or synthesis.
Possible or observed result: selected original text placed in prompt, with warnings that previous solutions may be wrong.
Implemented force: enforcing inclusion/order, advisory semantic reliance.
Epistemic authority and scope: imported/model-generated source warrant is not improved by similarity or display; selected text preserves candidate content, not proof status.
Operational authority: determines examples visible to generator; omitted raw pairs remain in corpus.
Behavioral-authority path: see RT-BAP-reference-context; per-query reference context.
Evidence source ID and local anchor: SRC-1, dynamic_cheatsheet/language_model.py; see route.
Claim IDs or none: RT-CLM-adaptive-memory.
Mismatch marker or none: none; caution text is a counterexample to assuming all retrieved answers are endorsed.
Gap/limit: embedding alignment assumed by API; relevance, correctness and obedience unobserved.
Route ID: RT-RTE-context-selection
Route function: content transformation
Architectural status: implemented
Object/candidate ID: EPI-OBJ-cheatsheet, EPI-OBJ-generator-output
Content/update relation: truth-apt transformation: indeterminate
Transition or check target: retrieval-synthesis curator builds custom sheet from old sheet, selected pairs and next question.
Evaluator/condition and domain: model requested to assess effectiveness and generalize; unlike cumulative review it runs before the current answer.
Activation and timing: see route; retrieval-synthesis only.
Possible or observed result: new model-proposed sheet or raw-pair fallback; old synthesized sheet is not the missing-tag fallback.
Implemented force: proposal generation, followed by separate EPI-RTE-sheet-admission.
Epistemic authority and scope: neither known semantic preservation nor established non-entailment without a candidate instance; no target-grounded acceptance.
Operational authority: current generator sees synthesis in place of raw selected pairs.
Behavioral-authority path: curator prompt advisory; extractor enforcing text replacement; generator advisory current-query guidance.
Evidence source ID and local anchor: SRC-1, dynamic_cheatsheet/language_model.py, prompts/curator_prompt_for_dc_retrieval_synthesis.txt; see route.
Claim IDs or none: RT-CLM-adaptive-memory.
Mismatch marker or none: reshaping/generalization goals do not determine actual transformation class.
Gap/limit: no retained criticism-to-revision trace inspected.
Route ID: RT-RTE-local-execution
Route function: check/evidence production
Architectural status: implemented
Object/candidate ID: EPI-OBJ-generator-output
Content/update relation: truth-apt transformation: indeterminate
Transition or check target: model-selected Python computation over whatever inputs the proposed code encodes.
Evaluator/condition and domain: local Python execution and stdout/error capture; see route for permission and recursion conditions.
Activation and timing: model request during generation; result returns in continuation before answer/curation.
Possible or observed result: numerical/text output or failure/timeout, not necessarily a solution check.
Implemented force: continuation receives result and request to finish/try alternatives; no compulsory rejection on error.
Epistemic authority and scope: execution can supply evidence within the executed program's domain; no source-truth, encoding-fidelity or transfer warrant. Not every execution is an evaluator of a solution.
Operational authority: permits model-directed continuation and subsequent sheet proposal informed by transcript.
Behavioral-authority path: local executor to generator continuation, advisory; then full output to curator and later raw-output consumers.
Evidence source ID and local anchor: SRC-1, dynamic_cheatsheet/language_model.py, dynamic_cheatsheet/utils/execute_code.py; see route.
Claim IDs or none: EPI-CLM-performance-gains.
Mismatch marker or none: executable result is not automatically a checked entailed domain conclusion.
Gap/limit: no concrete executed target program supplied for this analysis; no warranted-premise derivation asserted.
Route ID: RT-RTE-provider-execution
Route function: check/evidence production
Architectural status: implemented
Object/candidate ID: EPI-OBJ-generator-output
Content/update relation: truth-apt transformation: indeterminate
Transition or check target: provider-selected computation, if native session/tool request activates.
Evaluator/condition and domain: external tool implementation; see route.
Activation and timing: native generator branch, not ordinary curator calls.
Possible or observed result: returned text; structured tool-event details omitted from wrapper result.
Implemented force: returned provider text enters answer/curator pipeline.
Epistemic authority and scope: no inspected tool-level validation warrant beyond provider contract request.
Operational authority: generator may use returned text; local-execution flag does not veto native branch.
Behavioral-authority path: service response to generator output and downstream curator/raw-pair consumers, advisory, current and subsequent queries.
Evidence source ID and local anchor: SRC-1, dynamic_cheatsheet/language_model.py, text_generation/simple_unified_client.py; see route.
Claim IDs or none: none.
Mismatch marker or none: no complete tool lineage in returned text.
Gap/limit: domain and actual tool invocation not determinable from source requests alone.
Route ID: RT-RTE-score-answer
Route function: check/evidence production
Architectural status: implemented
Object/candidate ID: EPI-OBJ-score-result, EPI-OBJ-target
Content/update relation: truth-apt transformation: entailed derivation
Transition or check target: extracted final answer against task scorer predicate, not explanation, curator text or strategy transfer.
Evaluator/condition and domain: deterministic Python predicate: normalized AIME equality; MC letter/text matching; GameOf24 value tolerance and number-token multiset; equation number-string shape and numerical equality.
Activation and timing: after generation/curation in driver; later file traversal in evaluation notebook.
Possible or observed result: Boolean follows inspected predicate, conditional on inputs/program execution; no actual result calculated here.
Implemented force: counters/printed aggregates, not admission.
Epistemic authority and scope: predicate satisfaction only, conditional on target validity. MC substring acceptance can accept a negated target-option statement; that limits semantic correctness license.
Operational authority: evaluation runs and can fail before disk write; ordinary false result only leaves counters unchanged and does not reject sheet.
Behavioral-authority path: driver/notebook counters and console, enforcing arithmetic of reported totals, current evaluation; no score-to-model feedback.
Evidence source ID and local anchor: SRC-1, dynamic_cheatsheet/utils/evaluation.py, run_benchmark.py, EvaluatingResults.ipynb; see EPI-OBJ-score-result.
Claim IDs or none: EPI-CLM-performance-gains.
Mismatch marker or none: output scoring is not memory validation.
Gap/limit: extraction differs across consumers; causal benefit and explanation validity do not follow from a pass.
Route ID: RT-RTE-benchmark-cycle
Route function: retention
Architectural status: implemented
Object/candidate ID: RT-OBJ-output-dict, EPI-OBJ-cheatsheet, EPI-OBJ-generator-output
Content/update relation: no content change
Transition or check target: carry sheet/output list and serialize rows, irrespective of Boolean correctness.
Evaluator/condition and domain: driver assignment/file write; see route.
Activation and timing: handoff before score; disk rewrite after score.
Possible or observed result: latest sheet and prior outputs remain available for next round/query or resume.
Implemented force: actual input-state selection and persistence wired.
Epistemic authority and scope: retention confers no acceptance; row contains target, but later generator corpus uses final_output, not corrected target.
Operational authority: next invocation may rely on unvalidated retained text; continuation restores last non-null sheet.
Behavioral-authority path: see RT-BAP-reference-context, advisory beyond one query and through resume.
Evidence source ID and local anchor: SRC-1, run_benchmark.py; see route.
Claim IDs or none: RT-CLM-adaptive-memory.
Mismatch marker or none: retention is not lifecycle integration following acceptance.
Gap/limit: file/score exceptions can interrupt retention; no automatic semantic rollback or score-triggered withdrawal, as EPI-ABS-score-feedback establishes.
Route ID: EPI-ABS-score-feedback
Route function: lifecycle integration
Architectural status: no route found within boundary
Object/candidate ID: EPI-OBJ-cheatsheet
Content/update relation: no content change
Transition or check target: acceptance of a truth claim against explicit evidence/criterion followed by integration or withdrawal on a failed benchmark score.
Evaluator/condition and domain: none found in the inspected wrapper, extractor, CLI and evaluator cell-source consumers; see bounded search record.
Activation and timing: none found for this function; operational reuse occurs without it.
Possible or observed result: no acceptance record or score-driven sheet rejection in those paths.
Implemented force: none found for this function.
Epistemic authority and scope: does not establish absence of model-internal criticism or standalone checker capability.
Operational authority: no score-based block on later sheet supply.
Behavioral-authority path: none found for score-to-sheet feedback; existing text reuse remains independently wired.
Evidence source ID and local anchor: SRC-1, run_benchmark.py, dynamic_cheatsheet/language_model.py, dynamic_cheatsheet/utils/extractor.py, EvaluatingResults.ipynb; see record.
Claim IDs or none: EPI-CLM-verified-solutions.
Mismatch marker or none: operational use can precede any independently evidenced epistemic acceptance.
Gap/limit: bounded shipped-loop conclusion, not a negative about inaccessible provider reasoning or every auxiliary API.
System-claim versus route comparison
| Claim ID | Claimed operation or warrant | Claim source ID/anchor and evidence layer | Doctrine/design support | Implemented route IDs | Observed-run support | Causal support and design limits | Supported conclusion | Mismatch/unknown |
|---|---|---|---|---|---|---|---|---|
| RT-CLM-adaptive-memory | See record | SRC-1, README.md; doctrine/design |
Explicit cross-query reuse without parameter changes | RT-RTE-benchmark-cycle, RT-RTE-context-selection, RT-RTE-cumulative-update | No payload/trace assessed | Same endpoint supplies generator/curator; source-owned weight updates not found by supplied component inspection | Text-based adaptive input pathway implemented | Accumulated useful strategies and changed capacity not established by wiring |
| EPI-CLM-verified-solutions | See record | SRC-1, prompts/curator_prompt_for_dc_cumulative.txt; doctrine/design |
Correctness review and tested/effective entry selection requested | EPI-RTE-curator-review, EPI-RTE-sheet-admission, RT-RTE-score-answer | No acceptance trace inspected | Score checks answer after update; format controls replacement | Model asked to curate; code admits tagged proposal | Verified-entry warrant not enforced or observed; missing closing delimiter still admits |
| EPI-CLM-performance-gains | See record | SRC-1, README.md; reported operation |
Zero-shot, cumulative learning and task accuracy assertions | RT-RTE-context-selection, RT-RTE-local-execution, RT-RTE-score-answer | README report only; historical corpora uninspected | No inspected intervention/comparison establishes memory-specific effect, strategy transfer or component attribution | Claims have plausible implemented input and scoring pathways | Magnitude, mechanism, transfer and causal improvement remain unassessed |
Bounded conclusion
Dynamic Cheatsheet implements operational reuse of retained text, not a software-certified knowledge base. It imports problem data, labels, optional initial sheets and saved state with source warrant unknown; it preserves raw candidate outputs for later full-history/retrieval consumption and lets a model replace a carried sheet. Cosine similarity grants visibility, not correctness. Curation may change meaning or introduce new generalizations, but source-only inspection cannot individuate actual propositions or decide between compression, entailed derivation and ampliative conjecture for those model outputs. These conclusions follow RT-RTE-context-selection, RT-RTE-benchmark-cycle and EPI-OBJ-cheatsheet.
There are real but distinct checking paths. Local execution returns evidence about the selected program; hosted execution returns provider text with incomplete tool lineage; neither by itself validates problem encoding or broader strategies. Deterministic answer scoring derives a predicate result from an extracted answer and, where used, an imported target. Its license stops at the program's checked domain. In particular, multiple-choice text inclusion is not semantic entailment, and the notebook's extraction can select a different answer than runtime extraction. These are RT-RTE-local-execution, RT-RTE-provider-execution and EPI-OBJ-score-result, not interchangeable oracles.
The cumulative curator receives proposed solution text, including available execution transcript, and is asked to assess correctness and future usefulness. It does not receive the benchmark target or score through that update route. Its proposal is admitted by delimiters; false answer scores do not veto or withdraw it. Thus no inspected evidence-consuming acceptance decision licenses a new ampliative claim for a named future-use scope. No subsequent lifecycle integration following such acceptance is established. This does not deny that the model can check or criticize; it distinguishes the implemented request from an evidenced result and a consequential acceptance decision (EPI-RTE-curator-review, EPI-RTE-sheet-admission, EPI-ABS-score-feedback).
The implemented behavioral authority is substantial but advisory at semantic use: carried sheet and selected outputs enter later generator user-message context, while the extractor and caller enforce which text is supplied. The horizon includes later rounds, queries and resumed runs. Whole replacement can remove old errors, but can also remove correct content; logged history does not implement semantic rollback. Direct strategy/policy adaptation through natural-language guidance can occur without producing or accepting a truth-apt proposition. Evidence-responsive improvement remains a separate question, not a consequence of retention (RT-BAP-reference-context, RT-RTE-cumulative-update).
Localized rule text and computational update/read-back routes afford iterative guidance revision. Whether formulated theories are actually criticized, revised and used because of their content remains uninspected, as does retained criticism shaping later rounds. The wrapper supports a dispositional, improvement-directed change to its own future guidance, not source-grounded proof of exercised self-improvement: subsequent behavior causally depending on a particular evidence-shaped change is not established. Improved capacity, reflective two-way self-representation, autonomous performance of every theory-building operation and successful self-improvement remain independent, unestablished conclusions, not a bundled negative. Provider weights are separately opaque and not updated by inspected wrapper code (RT-CMP-language-model). The README's performance reports need inspected run/comparison evidence before attributing benefit or transferable mechanisms (EPI-CLM-performance-gains).
Shared records
Operative objects
EPI-OBJ-cheatsheet
Label: cheatsheet reference text
Part of: RT-OBJ-output-dict
Source-native identity: final_cheatsheet and its live carried string. Representational form: natural-language strategy/claim text and code interpreted by the generator/curator; delimiters are symbolic selection syntax, not validated per-entry schemas. Storage substrate: Python string, caller JSONL, optional initial file. This is the semantic part of the supplied result envelope, not a duplicate envelope. The text can contain truth-apt claims about applicability and examples as well as non-truth-apt instructions. SRC-1, dynamic_cheatsheet/language_model.py, prompts/curator_prompt_for_dc_cumulative.txt.
cheatsheet = new_cheatsheet ---
dynamic_cheatsheet/language_model.py:435-435
- Clearly state any assumptions, limitations, or dependencies (e.g., specific Python libraries or solution hacks). ---
prompts/curator_prompt_for_dc_cumulative.txt
Counts and Q references are requested prose. No fixed parser in the inspected wrapper/extractor checks individual entries, counts, reference support or scope. Their truth status therefore does not follow from being present.
EPI-OBJ-generator-output
Label: generator_output solution transcript
Part of: RT-OBJ-output-dict
Source-native identity: final_output/generator_output solution text; includes recursive local-execution transcript when that branch operates. Representational form: natural language and code, with symbolic answer tags; provider text does not expose all hosted events. Storage: Python string and caller JSONL. This is a material text part distinct from the sheet and the envelope. SRC-1, dynamic_cheatsheet/language_model.py, run_benchmark.py; closest execution records are RT-RTE-local-execution and RT-RTE-provider-execution.
current_output = f"{output_prefix}\n{code_execution_flag}\n\n{executed_code}" ---
dynamic_cheatsheet/language_model.pygenerator_outputs_so_far.append(output_dict["final_output"])
---
run_benchmark.py
EPI-OBJ-target
Label: original_target expected outcome
Source-native identity: dataset target, saved with result rows and passed to selected scoring functions. Form: natural-language/answer text, consumed symbolically by predicates. Storage: loaded dataset and JSONL envelope. Distinct from RT-OBJ-output-dict: imported oracle input, not the API's returned envelope; the driver augments that envelope. SRC-1, run_benchmark.py.
original_target = dataset[idx]["target"]
---
run_benchmark.py"target": original_target, ---
run_benchmark.py
This establishes import and routing, not label accuracy. GameOf24 uses the input numbers and computed target value 24 instead of trusting an answer label.
EPI-OBJ-score-result
Label: result Boolean task score
Source-native identity: local result Boolean and correctness counters. Representational form: symbolic Boolean/integer state with fixed consumer rules. Storage: transient driver/notebook variables and console totals; the inspected driver does not add result to the saved output dictionary. This is the product of RT-RTE-score-answer, not a duplicate route or the saved envelope. SRC-1, dynamic_cheatsheet/utils/evaluation.py, run_benchmark.py, EvaluatingResults.ipynb.
if result: correct_so_far += 1 total_so_far += 1 ---
run_benchmark.py
Scorer target/domain and limits: AIME compares output after punctuation/newline removal with provided target. GameOf24 checks cleaned expression value within 1e-3 of 24 and exact sorted token multiset after removing arithmetic symbols. Equation balancing checks operator-stripped number-string equality to the reference and numerical equality within 1e-6 to the target RHS. These do not establish explanation correctness. Multiple choice permits letter matches or inclusion of target option text:
if target_text and target_text in clean_answer: return True ---
dynamic_cheatsheet/utils/evaluation.py
Concrete implementation deduction, without execution: with input_text = "Options:\n(A) red\n(B) blue", target = "(A)", final_answer = "not red", cleaning gives target letter a, option extraction gives red, and substring acceptance returns True. The assertion that the answer is the target option is not thereby established. This narrows the scorer's license to its predicate, not arbitrary multiple-choice semantics.
Extraction also changes the object evaluated. Runtime selects the last opening tag, while notebook selects the first in the last step:
txt = response.split("
")[-1].strip() ---
dynamic_cheatsheet/utils/extractor.py" final_answer = model_output.split(\"
\")[1].split(\" \")[0].strip()\n",---
EvaluatingResults.ipynb:60-60
A response <answer>1</answer><answer>2</answer> therefore yields runtime 2 versus notebook 1, before task scoring. This is a deterministic source deduction, not an observed benchmark discrepancy.
Routes
EPI-RTE-curator-review
Label: Requested correctness assessment by curator
Part of: RT-RTE-cumulative-update
This isolates the proposed semantic check from that supplied route's generation/admission container. Endpoints: current question, full generator output and current sheet to curator model; proposed replacement text to extractor. Python owns timing; model proposes revisions and effectively chooses their semantic content. Computational inference rather than per-entry human review is wired. Operating modes: caller questions and benchmark sequence; update is unconditional each cumulative round or single hybrid pair, not score-triggered. Answer oracle: no reference target or score argument enters this prompt assembly. The check target is correctness/usefulness of the solution and retained strategies, not formatting. SRC-1, dynamic_cheatsheet/language_model.py, prompts/curator_prompt_for_dc_cumulative.txt.
- Immediate return: curator output text to extraction; no independently parsed correctness verdict.
- Later read-back: extracted proposal can replace sheet and reach later round/query through caller handoff.
- Delegated visibility: model sees current solution and prior sheet but not dataset target or score through this route.
- Selection predicate: cumulative/hybrid approach with curator template; default CLI supplies
(empty)unless configured. - Invalidation or expiry: new text can omit/replace previous content; no semantic expiry rule enforced.
- Activation or effect: prompt request and replacement pathway wired; successful criticism, correction and downstream behavioral activation unobserved.
- Evidence limits: model internals uninspected; an instruction to assess is not an assessment result or acceptance record.
- implementation conclusion status: wired
- operation conclusion status: uninspected
Before updating the cheatsheet, however, you should first assess the correctness of the provided solution and strategically incorporate code blocks, insights, and solutions into the new cheatsheet. Always aim to preserve and keep correct, useful, and illustrative solutions and strategies for future cheatsheets. ---
prompts/curator_prompt_for_dc_cumulative.txtcheatsheet_prompt = cheatsheet_template.replace("[[QUESTION]]", input_txt).replace("[[MODEL_ANSWER]]", generator_output).replace("[[PREVIOUS_CHEATSHEET]]", current_cheatsheet)
---
dynamic_cheatsheet/language_model.py:423-423
Guidance requests tested/effective entries and usage counters; it shapes the proposal but is not itself revised. Persisted output is the extracted sheet, not necessarily the rationale or a localized theory criticism. Rollback is missing-tag fallback only; logs may preserve older versions but no evidence-driven rollback consumer was found.
Theory account, conditional on sheet entries expressing formulated rules: whole units can be inspected/replaced, so condition 1 has an implementation conclusion status of afforded. Condition 2 has an implementation conclusion status of afforded for interpretation-dependent use, not observed dependence on a particular theory. Condition 3 has an operation conclusion status of uninspected: correctness review is requested, but no challenged proposition, result and blame placement leading to revision was inspected. Condition 4 has an implementation conclusion status of afforded through round/query handoff, but an operation conclusion status of uninspected for kept criticism shaping a next round. None is inferred from another. Addressability is textual whole-sheet replacement, with optional model-authored entry tags, not fixed per-assumption update machinery. Persistence horizon is later rounds/queries and caller resume. Under learning: improved future capacity remains uninspected; no inspected comparison attributes it to a change. Reflection and autonomous theory-building remain uninspected, rather than inferred from automated curation.
EPI-RTE-sheet-admission
Label: Tagged sheet extraction and replacement
Distinct identity comparison: this is the shared deterministic admission submechanism spanning RT-RTE-cumulative-update and retrieval-synthesis in RT-RTE-context-selection, not a replacement for either larger route. Endpoints: model response and fallback string to extracted live sheet. Owner: Python extract_cheatsheet and its callers. Model proposes arbitrary content; software chooses the substring; no human approval or oracle is required. SRC-1, dynamic_cheatsheet/utils/extractor.py, dynamic_cheatsheet/language_model.py.
- Immediate return: first opening-tag content up to first closing tag, or fallback.
- Later read-back: cumulative/hybrid sheet reaches next round/query; synthesized sheet reaches immediate generator and can be carried by caller.
- Delegated visibility: generator gets selected sheet, not a parsed correctness verdict or full curator reasoning.
- Selection predicate:
<cheatsheet>present; closing tag not required for successful split. - Invalidation or expiry: replaces entire live string; omissions vanish from sheet but may survive earlier logs or raw-output corpus.
- Activation or effect: enforcing string replacement wired; semantic endorsement and improved behavior not established.
- Evidence limits: extraction establishes text selection only, not that curator followed instructions or checked evidence.
- implementation conclusion status: wired
- operation conclusion status: uninspected
if "
" in response: try: txt = response.split(" ")[1].strip() txt = txt.split(" ")[0].strip() return txt---
dynamic_cheatsheet/utils/extractor.py
Concrete input trace, deduced from inspected implementation: response = "<cheatsheet>2+2=5", old_cheatsheet = "old" passes the opening-tag test, selects 2+2=5, finds no closing delimiter and returns that same substring. The false claim replaces the old sheet; there is no truth predicate in this function. response = "2+2=4" without the opening tag returns the supplied fallback despite its true arithmetic content. This separates syntactic admission from semantic acceptance without executing the target.
Trigger: curator response after update/synthesis; proposed change: whole sheet. Software veto is only missing-tag/exception fallback, not answer correctness. Recovery uses previous sheet for cumulative/hybrid, retrieved raw pairs for synthesis. Guidance resides in curator prompts, with no independently checked compliance gate. No revised production machinery is installed.
Claims
EPI-CLM-verified-solutions
Label: Verified solutions as curator objective
Distinct from broad RT-CLM-adaptive-memory: this claim concerns the warrant expected of retained entries, not just storage/reuse. Source: SRC-1, prompts/curator_prompt_for_dc_cumulative.txt, doctrine/design. Its imperative wording sets a normative selection condition; it does not report observed compliance.
The cheatsheet's purpose is to consolidate verified solutions, reusable strategies, and critical insights into a single, well-structured resource. ---
prompts/curator_prompt_for_dc_cumulative.txt
- Only include solutions and strategies that have been tested and proven effective. ---
prompts/curator_prompt_for_dc_cumulative.txt
EPI-CLM-performance-gains
Label: Zero-shot and benchmark improvement claims
Distinct from RT-CLM-adaptive-memory: isolates claimed measured benefit and attribution from parameter-preserving reuse architecture. SRC-1, README.md, doctrine/design for learning objective and reported operation for task gains. No causal experiment was independently assessed in this member.
Zero-Shot Learning: Improves performance without ground-truth labels or human feedback ---
README.mdPuzzles: GPT-4o's success rate on Game of 24 increased from approximately 10% to 99% after discovering and reusing Python-based solutions ---
README.md
Evidenced absences
EPI-ABS-score-feedback
Label: No score-driven memory veto in shipped loop
- implementation conclusion status: absent
Searched boundary: SRC-1 at the reviewed revision; full run_benchmark.py, dynamic_cheatsheet/language_model.py, dynamic_cheatsheet/utils/extractor.py, dynamic_cheatsheet/utils/evaluation.py, plus all cell source in EvaluatingResults.ipynb. Query/call-flow inspection: generation and curator arguments, assignments to cheatsheet/final_cheatsheet, uses of result, score dispatch, extractor calls, extract_solution callers and iteration consumers. Closest supplied records are RT-RTE-benchmark-cycle, RT-RTE-score-answer and RT-RTE-cumulative-update; this record isolates their absent score-to-memory feedback edge, not their implemented checking or retention routes.
The driver updates its live sheet before evaluation. Its ordinary Boolean result changes counters only; subsequent inputs are drawn from prior final_output and current sheet, not score/target-based corrections. Notebook scoring prints aggregate results. No failed-score sheet veto, claim withdrawal, acceptance record or semantic rollback consumer was found in these paths. This supports a bounded absence of score-grounded acceptance/integration, not absence of all possible model reasoning, imported human edits, external or auxiliary evaluation.
cheatsheet = output_dict["final_cheatsheet"] final_answer = output_dict["final_answer"]
---
run_benchmark.pyif result: correct_so_far += 1 total_so_far += 1 ---
run_benchmark.py
A counterexample sought was a later restoration/correction using targets. Resume instead restores saved sheet and final_output, while ordinary false scores still proceed to save and the next iteration. No automatic target substitution or correction is wired. Evaluation exceptions can abort before disk write; that is an execution failure, not a truth-sensitive rejection of the proposed memory.
Behavioral-authority paths
none declared in this member; see RT-BAP-reference-context.