Agent skill

Skill Gap Analysis

by devcodex-labs in devcodex-labs/devcodex

Skill 缺口与大语料分析 Owner — 当任务涉及项目/工作区产物扫描、能力盘点、缺少哪些 Skill、全量审查前规模判断、大目录分批、抽样深读、扫描恢复或自我进化候选发现时使用;要求先识别项目并形成规模决策,再进行有边界的证据扫描。

AGPL-3.0Auto-check passed

Install Skill Gap Analysis

skills CLI
$ npx skills add devcodex-labs/devcodex --skill skill-gap-analysis -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install devcodex-labs/devcodex skill-gap-analysis --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/devcodex-labs/devcodex.git skills-src && mkdir -p .claude/skills && cp -r skills-src/content/skills/skill-gap-analysis .claude/skills/skill-gap-analysis && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
skill-gap-analysis
GitHub stars
439
Token cost
~1.3k tokens
SKILL.md length
369 words
Files
3
Skills in repo
70
Repo updated
First seen
Licence
AGPL-3.0

At a glance

Skill 缺口与大语料分析 Owner — 当任务涉及项目/工作区产物扫描、能力盘点、缺少哪些 Skill、全量审查前规模判断、大目录分批、抽样深读、扫描恢复或自我进化候选发现时使用;要求先识别项目并形成规模决策,再进行有边界的证据扫描。

  • Works in 4 steps: 识别唯一 project / root /… → 只做 bounded inventory,显式排除… → 统计 relevantFileCount / parseableBytes /… → …
  • SKILL.md covers 职责, ProjectArtifactScaleRoutingGate, WorkspaceRootScanHygiene(C16 /… and TimeToFirstValueGate(TTFV · 与…, plus 7 more sections
  • Calls npm

What it does

Skill Gap Analysis is an agent skill from devcodex-labs/devcodex. Skill 缺口与大语料分析 Owner — 当任务涉及项目/工作区产物扫描、能力盘点、缺少哪些 Skill、全量审查前规模判断、大目录分批、抽样深读、扫描恢复或自我进化候选发现时使用;要求先识别项目并形成规模决策,再进行有边界的证据扫描。

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files (for example `agents/openai.yaml` and `intent.json`).

The repository describes itself as: Intent-driven AI coding workflow runtime for consistent context, skills, approvals, validation, and handoffs across six AI coding hosts. The licence is AGPL-3.0.

Example prompts

  • “/skill-gap-analysis”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. 识别唯一 project / root / activeRoot;未识别时停止,不得扫描整个工作区。
  2. 只做 bounded inventory,显式排除 node_modules/dist/cache/tmp/backup/smoke/deploy mirror 等派生产物。
  3. 统计 relevantFileCount / parseableBytes / largestFileBytes / directoryConcentration / derivedArtifactRatio / consumerFanOut。
  4. 形成 ScaleDecisionRecord,再允许内容读取或递归检索。

What it can do on your machine

Read from SKILL.md and the folder at commit 1dd4525. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • npm

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use npm, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Skill Gap Analysis loads about 1.3k tokens when it runs. Until then it costs about 35 tokens; SKILL.md has 369 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~35
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from devcodex-labs/devcodex at commit 1dd4525, republished under its AGPL-3.0 licence (© devcodex-labs). 369 words, ~1,342 tokens.

Download SKILL.mdSave it as .claude/skills/skill-gap-analysis/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
skill-gap-analysis
description
Skill 缺口与大语料分析 Owner — 当任务涉及项目/工作区产物扫描、能力盘点、缺少哪些 Skill、全量审查前规模判断、大目录分批、抽样深读、扫描恢复或自我进化候选发现时使用;要求先识别项目并形成规模决策,再进行有边界的证据扫描。

Skill Gap Analysis

职责

在分析、审查或能力盘点前先判断目标项目和语料规模,再选择一次性、分批、抽样深读或阻断路线;完成扫描后,把领域信号与现有 Skill Owner、消费者和验证路线交叉去重,形成可复证的缺口决策。

ProjectArtifactScaleRoutingGate

任何 broad scan 前必须按顺序执行:

  1. 识别唯一 project / root / activeRoot;未识别时停止,不得扫描整个工作区。
  2. 只做 bounded inventory,显式排除 node_modules/dist/cache/tmp/backup/smoke/deploy mirror 等派生产物。
  3. 统计 relevantFileCount / parseableBytes / largestFileBytes / directoryConcentration / derivedArtifactRatio / consumerFanOut。
  4. 形成 ScaleDecisionRecord,再允许内容读取或递归检索。

WorkspaceRootScanHygiene(C16 / PI-20260724-01 · 范围与成本规则)

🔴 未绑定唯一项目前,禁止对 workspace/monorepo 根发起递归 inventory。项目路径已知时,禁止再从 workspace 根 -Recurse 查找。

禁止允许
Get-ChildItem <workspaceRoot> -Recurse(含 -Depth ≥1、按名 Filter 全树搜)list_dir 仅一层;Test-Path <workspaceRoot>/<project>
dir /s <workspaceRoot>、find <workspaceRoot> 无项目前缀在已绑定 project root 内有界 Recurse,且排除 node_modules/dist
为「找项目」扫整个 E:\Worker 等 monorepo 根用户 @path / 已知子目录名 / Profile inventory
inventory 展开 node_modules、文档站 doc_build、巨型 dist显式 -Exclude / 工具默认尊重 gitignore 的列表

机器探针:scripts/lib/host-parity-scorecard.js → classifyWorkspaceRootScanSample(workspace-root-recurse = 范围/成本缺陷)。Hook 侧对命中 workspace 根 + Recurse 的 shell 只发出 advisory;执行权限由宿主及其用户配置决定(见 lifecycle-dangerous-command)。

TimeToFirstValueGate(TTFV · 与 compliance/C16 联防)

非 chat 在入口检查与最小 ContextReadPlan 之后,同一用户可见回复必须至少交付其一,否则本轮视为扫描/准备违规:

  1. 可确认的半屏范围卡(路径/批次/排除项);或
  2. 首批 finding / 分析结论 / 可执行方案要点;或
  3. 明确阻断(项目不明、权限、环境缺失)+ 恢复动作。

禁止:整轮只读 Skill 百科、只跑全库 inventory、或只写超长需求概括却零交付。用户明确「直接开审/跳过确认」时跳过范围确认,立即 B1 交付。

ProgressReportFastPath(PI-20260725-01 · TTFV 进度查询特化)

🔴 用户问「进度 / 发版到哪了 / 验证状态」且已点名项目时,禁止 workspace 根 inventory 与模糊 task 名阻塞首答。

步骤要求
绑定立即绑定 .devcodex/<project>/ 与源码目录;路径直达
真相源顺序① verification/issues/README(或问题总台账)② fixed-awaiting-rerun-classification(若有)③ profile 发布/项目检查点 ④ SUMMARY 近行 ⑤ 仅不足时再读 05-实施进度/报告
首轮交付需求定位 → 进度数字表 → 当前阻断 → 一句话结论
失败同 TTFV 违约;探针 classifyProgressReportFastPathSample → progress-fail

机器探针:scripts/lib/executable-absorption-gates.js → classifyProgressReportFastPathSample;npm run test:executable-absorption-gates。

decision默认判定执行
single-pass全部满足 ≤50 files、≤2 MiB、largest≤256 KiB、fan-out≤10,且用户未提示大目录一次处理,仍保留排除策略
batched任一中等规模、fan-out>10、控制面联动或用户提示目录大按 namespace/目录/文件预算分批,逐批写 checkpoint
sampled+deep-read>500 files、>20 MiB、derived ratio>30% 或目录极端集中全量 inventory + 强语义检索 + 代表文件深读;禁止声称逐字全读
blocked项目/root 不唯一、排除边界不可信、权限/文件系统错误停止 broad scan,先恢复边界

项目 Profile 可以配置更保守阈值,不得放宽上述默认边界;用户明确“大目录/文件很多”时不得降为 single-pass。

ScaleDecisionRecord

至少记录:project、root、activeRoot、inventoryCommand、六项规模指标、decision、reason、exclusionPolicy、batchBudget、checkpointPath、timeoutRetry、invalidRunPolicy。

  • 非 single-pass 缺 checkpointPath 或 batch budget 时不得继续。
  • timeout、错误 glob、派生产物污染或无法解释的数量跳变必须标记 invalid/discarded,不能进入结论。
  • 检查点状态使用 not-started / running / accepted / invalid / blocked;恢复只从最后一个 accepted 批次继续。
Show full SKILL.md (142 more words)Show less

Skill 缺口分析流程

  1. 生成 WorkspaceCorpusManifest 与 ExclusionPolicy。
  2. 按规模决策执行 BatchEvidenceLedger,每批记录输入、命令、文件数、有效信号和异常。
  3. 宽口径召回后执行强语义复扫、词边界校准、代表文件深读和历史镜像降权。
  4. 建立 ExistingSkillCoverageMatrix:候选 → 最接近 Owner → 未闭合边界 → current consumer → validation。
  5. 执行 CommonNormGeneralizationGate 与消费者证明;项目局部信号标为 project-local / case-evidence-only。
  6. 为每个真正缺口冻结 trigger、ownedArtifacts、consumerSync、validationRoute 和负向样例。
  7. 至少完成两轮维度不同的 omission-only 零新增,写入 ConvergenceRecord。

输出产物

产物必填内容
WorkspaceCorpusManifestnamespace、路径类型、文件/字节、派生边界
ScaleDecisionRecord规模指标、四态决策、预算与理由
BatchEvidenceLedger批次、checkpoint、命令、状态、invalid-run
ExistingSkillCoverageMatrix候选与现有 Owner 的覆盖/重叠/缺口
CapabilityGapDecisionnew-skill / existing-subgate / docs-only / reject
ConvergenceRecord每轮维度增量、新增数、连续零新增

所有覆盖结论同时执行 audit-common 的 ReviewCoverageClaimIntegrityGate。WorkspaceCorpusManifest 只能证明 inventory-covered;关键词检索只能证明 machine-scanned;代表文件深读必须明确 sampledSet/unreadSet/inferenceBoundary。只有逐文件 FileEvidenceLedger 才能声明逐字全读。

与 incremental-project-analysis 分界

本 Skillincremental-project-analysis
规模路由、corpus inventory、Skill 缺口 vs Owner知识快照、digest 失效、BatchProgress 强制交付、GlobalBacklog、精度合同、双层验证
「怎么分批扫、缺什么能力」「扫完的事实如何复用、如何对用户分批交付与综合」

batched / sampled+deep-read 的 analyze 路径在形成 ScaleDecision 后应同时调用 incremental-project-analysis 的交付与精度门禁;本 Skill 不把快照状态机整坨并入。

反模式

  • 未识别项目就从 workspace root 递归扫描。
  • 项目名已知仍对 monorepo 根 Get-ChildItem -Recurse -Depth N 找目录(PI-20260724-01 复发样例)。
  • 先全量扫描超时,再补写“应该分批”。
  • 把备份、安装包、浏览器 Profile、translation cache 或 lockfile 当能力证据。
  • 只按关键词计数,不读代表样本、不反查现有 Skill。
  • 用抽样深读结果宣称“逐字审查所有文件”。
  • 同一批次失败后继续沿用部分输出,或用后续成功命令覆盖前序失败。
  • 做完分批扫描却不调用 incremental Skill,导致无 ProgressCard / 无快照 / 假完整主题清单。
  • 首轮用户可见回复只有流程/Skill 预热、无范围卡/finding/阻断(TTFV 失败)。

验证

至少包含:小项目 single-pass 正向、用户大目录强制 batched、>500 文件 sampled+deep-read、unresolved project blocked、错误 OR glob、派生污染、timeout 无 checkpoint、历史 already-fixed 未去重等正负向样例。

© devcodex-labs, AGPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files in content/skills/skill-gap-analysis of devcodex-labs/devcodex.

  • SKILL.md
  • agents/openai.yaml
  • intent.json

Open the folder on GitHubat commit 1dd4525

Compare with similar skills

Skill Gap Analysis next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Skill Gap Analysis compared with similar skills
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Skill Gap Analysissickn33/agentic-awesome-skills47k1 repos~3.6kAutomated safety check: PassMIT
Gap Surfaceranthropics/claude-for-legal9.6k1 repos~3.7kAutomated safety check: PassApache-2.0
Test Gapsruvnet/ruflo74k—~214Automated safety check: PassMIT
Reg Gap Analysisanthropics/claude-for-legal9.6k3 repos~3.7kAutomated safety check: PassApache-2.0

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Questions about Skill Gap Analysis

What does Skill Gap Analysis do?

Skill 缺口与大语料分析 Owner — 当任务涉及项目/工作区产物扫描、能力盘点、缺少哪些 Skill、全量审查前规模判断、大目录分批、抽样深读、扫描恢复或自我进化候选发现时使用;要求先识别项目并形成规模决策,再进行有边界的证据扫描。. Skill Gap Analysis is an agent skill from devcodex-labs/devcodex.

How do I install Skill Gap Analysis in Claude Code?

Run `npx skills add devcodex-labs/devcodex --skill skill-gap-analysis -a claude-code`. Or copy the skill folder (content/skills/skill-gap-analysis in devcodex-labs/devcodex) into .claude/skills/skill-gap-analysis in your project. Claude Code loads it when a task matches its description.

How do I install Skill Gap Analysis in Codex?

Run `npx skills add devcodex-labs/devcodex --skill skill-gap-analysis -a codex`. Or copy the skill folder (content/skills/skill-gap-analysis in devcodex-labs/devcodex) into .agents/skills/skill-gap-analysis in your project. Codex loads it when a task matches its description.

Can I use Skill Gap Analysis in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add devcodex-labs/devcodex --skill skill-gap-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/skill-gap-analysis, .gemini/skills/skill-gap-analysis, .github/skills/skill-gap-analysis and .opencode/skills/skill-gap-analysis in your project.

What does Skill Gap Analysis need to run?

Going by SKILL.md and its folder, Skill Gap Analysis needs the command-line tools its instructions call (npm).

Does Skill Gap Analysis access the network?

SKILL.md contains no URLs. Its commands use npm, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Skill Gap Analysis safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Skill Gap Analysis use?

Skill Gap Analysis is published under the AGPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Skill Gap Analysis use?

About 1.3k tokens (SKILL.md is roughly 5.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Skill Gap Analysis?

Skills that share tags, products or a category with Skill Gap Analysis: Gaps (anthropics/claude-for-legal, 9.6k stars), Skill Gap Analysis (sickn33/agentic-awesome-skills, 47k stars), Gap Surfacer (anthropics/claude-for-legal, 9.6k stars) and Test Gaps (ruvnet/ruflo, 74k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Skill Gap Analysis?

devcodex-labs (a GitHub organization) maintains it in devcodex-labs/devcodex, which has 439 GitHub stars. The repository holds 70 skills in this directory. The repository was last updated on September 17, 2026.

Source: devcodex-labs/devcodex on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.