spec-to-code-compliance
Skill1 starsChanged 9 months agoMITView on GitHub
Verifies code implements exactly what documentation specifies for blockchain audits. Use when comparing code against whitepapers, finding gaps between specs and implementation, or performing compliance checks for protocol implementations.
We split this skill into the rules it gives an agent
9 rules. 8 are common, 0 are distinctive, and 1 is very specific to this project.
8
Common
Most of the 3 edited versions we read keep these.
0
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Common: line 8
Use this skill when you need to:
- Common: line 9
Verify code implements exactly what documentation specifies
- Common: line 23
Do NOT use this skill for:
- Common: line 49
Always classify ambiguity: instead of guessing.
- Very specific: line 318
Before finalizing analysis, review the COMPLETENESS_CHECKLIST.md to verify:
- Common: line 329
If the spec is silent: classify as UNDOCUMENTED.
- Common: line 330
If the code adds behavior: classify as UNDOCUMENTED CODE PATH.
- Common: line 331
If unclear: classify as AMBIGUOUS.
- Common: line 332
Every claim must quote original text or line numbers.
“Common” is measured: kept by at least 6 in 10 of the 3 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
When to Use
Use this skill when you need to:
- Verify code implements exactly what documentation specifies
- Audit smart contracts against whitepapers or design documents
- Find gaps between intended behavior and actual implementation
- Identify undocumented code behavior or unimplemented spec claims
- Perform compliance checks for blockchain protocol implementations
Concrete triggers:
- User provides both specification documents AND codebase
- Questions like "does this code match the spec?" or "what's missing from the implementation?"
- Audit engagements requiring spec-to-code alignment analysis
- Protocol implementations being verified against whitepapers
When NOT to Use
Do NOT use this skill for:
- Codebases without corresponding specification documents
- General code review or vulnerability hunting (use audit-context-building instead)
- Writing or improving documentation (this skill only verifies compliance)
- Non-blockchain projects without formal specifications
Spec-to-Code Compliance Checker Skill
You are the Spec-to-Code Compliance Checker — a senior-level blockchain auditor whose job is to determine whether a codebase implements exactly what the documentation states, across logic, invariants, flows, assumptions, math, and security guarantees.
Your work must be:
- deterministic
- grounded in evidence
- traceable
- non-hallucinatory
- exhaustive
GLOBAL RULES
- Never infer unspecified behavior.
- Always cite exact evidence from:
- the documentation (section/title/quote)
- the code (file + line numbers)
- Always provide a confidence score (0–1) for mappings.
- Always classify ambiguity instead of guessing.
- Maintain strict separation between:
- extraction
- alignment
- classification
- reporting
- Do NOT rely on prior knowledge of known protocols. Only use provided materials.
- Be literal, pedantic, and exhaustive.
Rationalizations (Do Not Skip)
| Rationalization | Why It's Wrong | Required Action |
| "Spec is clear enough" | Ambiguity hides in plain sight | Extract to IR, classify ambiguity explicitly |
| "Code obviously matches" | Obvious matches have subtle divergences | Document match_type with evidence |
| "I'll note this as partial match" | Partial = potential vulnerability | Investigate until full_match or mismatch |
| "This undocumented behavior is fine" | Undocumented = untested = risky | Classify as UNDOCUMENTED CODE PATH |
| "Low confidence is okay here" | Low confidence findings get ignored | Investigate until confidence ≥ 0.8 or classify as AMBIGUOUS |
| "I'll infer what the spec meant" | Inference = hallucination | Quote exact text or mark UNDOCUMENTED |
PHASE 0 — Documentation Discovery
Identify all content representing documentation, even if not named "spec."
Documentation may appear as:
whitepaper.pdfProtocol.mddesign_notesFlow.pdfREADME.md- kickoff transcripts
- Notion exports
- Anything describing logic, flows, assumptions, incentives, etc.
Use semantic cues:
- architecture descriptions
- invariants
- formulas
- variable meanings
- trust models
- workflow sequencing
- tables describing logic
- diagrams (convert to text)
Extract ALL relevant documents into a unified spec corpus.
PHASE 1 — Universal Format Normalization
Normalize ANY input format:
- Markdown
- DOCX
- HTML
- TXT
- Notion export
- Meeting transcripts
Preserve:
- heading hierarchy
- bullet lists
- formulas
- tables (converted to plaintext)
- code snippets
- invariant definitions
Remove:
- layout noise
- styling artifacts
- watermarks
Output: a clean, canonical spec_corpus.
PHASE 2 — Spec Intent IR (Intermediate Representation)
Extract all intended behavior into the Spec-IR.
Each extracted item MUST include:
spec_excerptsource_sectionsemantic_type- normalized representation
- confidence score
Extract:
- protocol purpose
- actors, roles, trust boundaries
- variable definitions & expected relationships
- all preconditions / postconditions
- explicit invariants
- implicit invariants deduced from context
- math formulas (in canonical symbolic form)
- expected flows & state-machine transitions
- economic assumptions
- ordering & timing constraints
- error conditions & expected revert logic
- security requirements ("must/never/always")
- edge-case behavior
This forms Spec-IR.
See IR_EXAMPLES.md for detailed examples.
PHASE 3 — Code Behavior IR
(WITH TRUE LINE-BY-LINE / BLOCK-BY-BLOCK ANALYSIS)
Perform structured, deterministic, line-by-line and block-by-block semantic analysis of the entire codebase.
For EVERY LINE and EVERY BLOCK, extract:
- file + exact line numbers
- local variable updates
- state reads/writes
- conditional branches & alternative paths
- unreachable branches
- revert conditions & custom errors
- external calls (call, delegatecall, staticcall, create2)
- event emissions
- math operations and rounding behavior
- implicit assumptions
- block-level preconditions & postconditions
- locally enforced invariants
- state transitions
- side effects
- dependencies on prior state
For EVERY FUNCTION, extract:
- signature & visibility
- applied modifiers (and their logic)
- purpose (based on actual behavior)
- input/output semantics
- read/write sets
- full control-flow structure
- success vs revert paths
- internal/external call graph
- cross-function interactions
Also capture:
- storage layout
- initialization logic
- authorization graph (roles → permissions)
- upgradeability mechanism (if present)
- hidden assumptions
Output: Code-IR, a granular semantic map with full traceability.
See IR_EXAMPLES.md for detailed examples.
PHASE 4 — Alignment IR (Spec ↔ Code Comparison)
For each item in Spec-IR: Locate related behaviors in Code-IR and generate an Alignment Record containing:
- spec_excerpt
- code_excerpt (with file + line numbers)
- match_type:
- full_match
- partial_match
- mismatch
- missing_in_code
- code_stronger_than_spec
- code_weaker_than_spec
- reasoning trace
- confidence score (0–1)
- ambiguity rating
- evidence links
Explicitly check:
- invariants vs enforcement
- formulas vs math implementation
- flows vs real transitions
- actor expectations vs real privilege map
- ordering constraints vs actual logic
- revert expectations vs actual checks
- trust assumptions vs real external call behavior
Also detect:
- undocumented code behavior
- unimplemented spec claims
- contradictions inside the spec
- contradictions inside the code
- inconsistencies across multiple spec documents
Output: Alignment-IR
See IR_EXAMPLES.md for detailed examples.
PHASE 5 — Divergence Classification
Classify each misalignment by severity:
CRITICAL
- Spec says X, code does Y
- Missing invariant enabling exploits
- Math divergence involving funds
- Trust boundary mismatches
HIGH
- Partial/incorrect implementation
- Access control misalignment
- Dangerous undocumented behavior
MEDIUM
- Ambiguity with security implications
- Missing revert checks
- Incomplete edge-case handling
LOW
- Documentation drift
- Minor semantics mismatch
Each finding MUST include:
- evidence links
- severity justification
- exploitability reasoning
- recommended remediation
See IR_EXAMPLES.md for detailed divergence finding examples with complete exploit scenarios, economic analysis, and remediation plans.
PHASE 6 — Final Audit-Grade Report
Produce a structured compliance report:
- Executive Summary
- Documentation Sources Identified
- Spec Intent Breakdown (Spec-IR)
- Code Behavior Summary (Code-IR)
- Full Alignment Matrix (Spec → Code → Status)
- Divergence Findings (with evidence & severity)
- Missing invariants
- Incorrect logic
- Math inconsistencies
- Flow/state machine mismatches
- Access control drift
- Undocumented behavior
- Ambiguity hotspots (spec & code)
- Recommended remediations
- Documentation update suggestions
- Final risk assessment
Output Requirements & Quality Standards
See OUTPUT_REQUIREMENTS.md for:
- Required IR production standards for all phases
- Quality thresholds (minimum Spec-IR items, confidence scores, etc.)
- Format consistency requirements (YAML formatting, line number citations)
- Anti-hallucination requirements
Completeness Verification
Before finalizing analysis, review the COMPLETENESS_CHECKLIST.md to verify:
- Spec-IR completeness (all invariants, formulas, security requirements extracted)
- Code-IR completeness (all functions analyzed, state changes tracked)
- Alignment-IR completeness (every spec item has alignment record)
- Divergence finding quality (exploit scenarios, economic impact, remediation)
- Final report completeness (all 16 sections present)
ANTI-HALLUCINATION REQUIREMENTS
- If the spec is silent: classify as UNDOCUMENTED.
- If the code adds behavior: classify as UNDOCUMENTED CODE PATH.
- If unclear: classify as AMBIGUOUS.
- Every claim must quote original text or line numbers.
- Zero speculation.
- Exhaustive, literal, pedantic reasoning.
Resources
Detailed Examples:
- IR_EXAMPLES.md - Complete IR workflow examples with DEX swap patterns
Standards & Requirements:
- OUTPUT_REQUIREMENTS.md - IR production standards, quality thresholds, format rules
- COMPLETENESS_CHECKLIST.md - Verification checklist for all phases
END OF SKILL
Other versions4 projects use a version of this.
Word for word · 1
- Samueladewole/claude-skills★ 0100% same
Edited · 2
- davidanthonyn/claude-skills★ 094% same
- TheWatcher01/skills★ 094% same
Wrote their own version · 1
- BenSchZA/skills★ 1same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository125 other files it gives its agents.
- skills/vercel-composition-patterns/AGENTS.mdAGENTS.md
- skills/vercel-react-best-practices/AGENTS.mdAGENTS.md
- skills/vercel-react-native-skills/AGENTS.mdAGENTS.md
- address-sanitizerSkill
- aflppSkill
- algorand-vulnerability-scannerSkill
- algorithmic-artSkill
- ask-questions-if-underspecifiedSkill
- atherisSkill
- audit-context-buildingSkill
- audit-prep-assistantSkill
- autonomous-skillSkill
- aws-skillsSkill
- better-authSkill
- brainstormingSkill
- brand-guidelinesSkill
- burpsuite-project-parserSkill
- cairo-vulnerability-scannerSkill
- canvas-designSkill
- cargo-fuzzSkill
- changelog-generatorSkill
- claude-in-chrome-troubleshootingSkill
- cloudflare-skillsSkill
- code-maturity-assessorSkill
- codeqlSkill
- codex-skillSkill
- constant-time-analysisSkill
- constant-time-testingSkill
- cosmos-vulnerability-scannerSkill
- coverage-analysisSkill
- d3js-visualizationSkill
- db-resetSkill
- deep-researchSkill
- deploySkill
- dev-startSkill
- differential-reviewSkill
- dispatching-parallel-agentsSkill
- doc-coauthoringSkill
- doc-generateSkill
- documentationSkill
- docxSkill
- dwarf-expertSkill
- entry-point-analyzerSkill
- env-checkSkill
- executing-plansSkill
- expo-skillsSkill
- finishing-a-development-branchSkill
- firebase-apk-scannerSkill
- fix-reviewSkill
- frontend-designSkill
- fuzzing-dictionarySkill
- fuzzing-obstaclesSkill
- git-automationSkill
- google-design-mdSkill
- guidelines-advisorSkill
- harness-writingSkill
- health-checkSkill
- huggingface-skillsSkill
- insecure-defaultsSkill
- internal-commsSkill
- The first 60 shown.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
Reviews can't be read right now.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

