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spec-to-code-compliance规范与代码合规性

Agent Skill

spec-to-code-compliance 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

376

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GitHub Stars

18,325

下载量

132
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:spec-to-code-compliance(规范与代码合规性)
来源仓库:https://github.com/elizaos/eliza
仓库路径:skills/spec-to-code-compliance
安装命令:
npx skills add https://github.com/elizaos/eliza --skill spec-to-code-compliance
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/elizaos/eliza --skill spec-to-code-compliance

简介

用于验证代码与文档规范的一致性。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

  • 适合审计智能合约或区块链协议实现是否符合设计文档。
  • 可识别未实现的功能、行为偏差或缺失的合规检查项。
  • 需同时提供规格文档和代码库才能触发分析。
  • spec-to-code-compliance 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

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 without a spec-to-code alignment task
  • 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:

1. extraction 2. alignment 3. classification 4. reporting

  • Do NOT rely on prior knowledge of known protocols. Only use provided materials.
  • Be literal, pedantic, and exhaustive.

Rationalizations (Do Not Skip)

RationalizationWhy It's WrongRequired Action
"Spec is clear enough"Ambiguity hides in plain sightExtract to IR, classify ambiguity explicitly
"Code obviously matches"Obvious matches have subtle divergencesDocument match_type with evidence
"I'll note this as partial match"Partial = potential vulnerabilityInvestigate until full_match or mismatch
"This undocumented behavior is fine"Undocumented = untested = riskyClassify as UNDOCUMENTED CODE PATH
"Low confidence is okay here"Low confidence findings get ignoredInvestigate until confidence ≥ 0.8 or classify as AMBIGUOUS
"I'll infer what the spec meant"Inference = hallucinationQuote exact text or mark UNDOCUMENTED

PHASE 0 — Documentation Discovery

Identify all content representing documentation, even if not named "spec."

Documentation may appear as:

  • whitepaper.pdf
  • Protocol.md
  • design_notes
  • Flow.pdf
  • README.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:

  • PDF
  • 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_excerpt
  • source_section
  • semantic_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:

  1. Executive Summary
  2. Documentation Sources Identified
  3. Spec Intent Breakdown (Spec-IR)
  4. Code Behavior Summary (Code-IR)
  5. Full Alignment Matrix (Spec → Code → Status)
  6. Divergence Findings (with evidence & severity)
  7. Missing invariants
  8. Incorrect logic
  9. Math inconsistencies
  10. Flow/state machine mismatches
  11. Access control drift
  12. Undocumented behavior
  13. Ambiguity hotspots (spec & code)
  14. Recommended remediations
  15. Documentation update suggestions
  16. 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:

Standards & Requirements:


END OF SKILL

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能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

38.82%
按下载量换算51

Claude

27.57%
按下载量换算36

Cursor

16.69%
按下载量换算22

Gemini CLI

9.84%
按下载量换算13

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

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