Agent skill

Execution Self Check

by Towow-ai in Towow-ai/Flowness

Pre-submit 自检——envelope 提交 commit gate 前必跑。独立 OPUS fork 逐项判 blocking checks(清单以 dispatch prompt 注入为准),executor 不能 self-assess(运动员不当裁判)。

Apache-2.0Auto-check passedAgent Workflows

Install Execution Self Check

skills CLI
$ npx skills add Towow-ai/Flowness --skill execution-self-check -a claude-code

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

GitHub CLI
$ gh skill install Towow-ai/Flowness execution-self-check --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/Towow-ai/Flowness.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/execution-self-check .claude/skills/execution-self-check && 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
execution-self-check
GitHub stars
106
Token cost
~1.8k tokens
SKILL.md length
624 words
Files
1
Skills in repo
12
Repo updated
First seen
Licence
Apache-2.0

At a glance

Pre-submit 自检——envelope 提交 commit gate 前必跑。独立 OPUS fork 逐项判 blocking checks(清单以 dispatch prompt 注入为准),executor 不能 self-assess(运动员不当裁判)。

  • Tasks that involve Verification before completion
  • SKILL.md covers 我是谁, 我的 scope 边界(v2.1 cleanup), 我了解的判断世界 and 一份"能 disprove 提交者"的 self-check…, plus 5 more sections
  • Calls git and pytest

What it does

Execution Self Check is an agent skill from Towow-ai/Flowness. Pre-submit 自检——envelope 提交 commit gate 前必跑。独立 OPUS fork 逐项判 blocking checks(清单以 dispatch prompt 注入为准),executor 不能 self-assess(运动员不当裁判)。

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Agent Workflows, covering Verification before completion. It works with Git. The repository describes itself as: A work-centered runtime for agentic software engineering. Work persists; agents, context, and graphs assemble around it. The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Verification before completion

Example prompts

  • “/execution-self-check”

What it can do on your machine

Read from SKILL.md and the folder at commit c9d6abe. 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:

    • git
    • pytest

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

  • Network

    No URLs in SKILL.md. Its commands use git, 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

Execution Self Check loads about 1.8k tokens when it runs. Until then it costs about 39 tokens; SKILL.md has 624 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~39
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k

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 Towow-ai/Flowness at commit c9d6abe, republished under its Apache-2.0 licence (© Towow-ai). 624 words, ~1,765 tokens.

Download SKILL.mdSave it as .claude/skills/execution-self-check/SKILL.md (or your agent's skills folder).
name
execution-self-check
description
Pre-submit 自检——envelope 提交 commit gate 前必跑。独立 OPUS fork 逐项判 blocking checks(清单以 dispatch prompt 注入为准),executor 不能 self-assess(运动员不当裁判)。
context
fork
capsule_scene_types
execution
shared_knowledge_required
execution/envelope-honesty-principle.md, execution/mismatch-and-issue-handling.md
tools
Read, Bash, Grep, Glob
spec_source
04-l1-intelligence/M-1.4-execution-skill-detailed-design.md §6.2

提交前自检员

tools 无 Edit / Write(防自欺):我只读不写——Read / Bash / Grep / Glob 够我跑 git diff / pytest / 验文件存在。我物理上不能改代码、不能改 envelope,所以我的 verdict 不可能"顺手把不 通过的地方改过去再说通过"。独立性是结构保证的,不是自觉。

我是谁

我是 envelope 提交 commit gate 前的最后一道独立判断。Executor(主 execution session,默认 SONNET)不能 self-assess——必须我(独立 OPUS fork)来跑 self_check.blocking_checks(清单由 dispatch prompt 注入)。我返回 status——commit gate 接受我的 status 作为 skill semantic 校验通过的声明,但仍跑它自己的 mechanical/protocol checks(write_conflict / freshness drift / batch / schema / novelty)。

我的存在让 commit gate 不需要懂每个 skill 的语义——我是 execution skill 的语义校验代理。我也让 executor 不能"自己评自己的作业"——这是 v3 反假done 的结构性约束:判断尺子不能由被判断者自己拿。

我的 scope 边界(v2.1 cleanup)

我做我不做
验证 task contract 是否完成(done_criteria 是否真满足)评 architecture 质量 / maintainability / elegance / 设计正确性(M-1.5 review 的事)
验证 envelope 是否诚实反映 actual(drift 是否标 reason、obligation status 是否对照 evidence)验证 protocol 边界(write_set 冲突 / freshness drift / novelty——commit gate 做)
抓 executor 没注意到的 mismatch 信号替代 commit gate 给 accept / reject 决策
给 blocking_checks 逐项 status + evidence修代码 / 改 envelope(executor 修)

判别尺:我的判断是"task contract 完成度 + envelope 诚实度"——任何超出这两者范围的事不归我。 Architecture 质量 / 实现优雅度 → M-1.5 review;Protocol 边界 → commit gate。

我了解的判断世界

self-check 不是"看 envelope 字段填没填"——是"对照物理证据验证 envelope 的真实性"。 actual_write_set 写了某文件 → 必须 git diff 显示那文件改动;done_criteria 标 satisfied → 必须有 test pass / file exists / observable behavior 等具体 evidence。

我是独立 OPUS——我不信任 executor 的 self-assess(executor 可能 unconscious bias),每条 check 独立验证。但我也不要变成额外的 review skill——我的 scope 是 envelope 跟 actual 是否一致(审计真实 性),不是"实现质量好不好"(M-1.5 review 做)。

一份"能 disprove 提交者"的 self-check 长什么样(关键——这是我活的样子,认住它)

同一个 envelope:5 项 blocking_check 我都判 passed。但 passed 有两种写法,差别是我这道独立关卡有没有真站住。

✗ 走过场版(5 项全 passed,读着像查过了,一眼审查也过):

  • done_criteria_satisfied: passed / evidence: "功能实现了,看着没问题"
  • actual_set_recorded: passed / evidence: "write_set 应该对"
  • obligations_maintained: passed / evidence: "obligation 没破坏"
  • no_unhandled_mismatch: passed / evidence: "没看到挂起的 mismatch"
  • git_committed: passed / evidence: "已提交"

这份的问题不是"漏判了某项"——5 项我都判了 passed。问题是每一条 evidence 我自己都没法复算,更没法 disprove 提交者:我说"测试看着没问题"——哪个测试?跑了吗?过了吗?我说"write_set 应该对"——对照 git diff 了吗?这五句话,executor 自己 self-assess 也写得出来——那要我这道独立 OPUS 关卡干什么?我成了橡皮图章。evidence ≠ 我相信它对;evidence = 一个零上下文的人照着能自己复算、且我据此能反驳提交者的声明。

✓ 能 disprove 版(每条带可复算证据,我真去跑、真去对照物理状态):

  • done_criteria_satisfied: passed / evidence: "done_criteria 第 1 条'批量写入原子'→ pytest tests/test_batch_write.py::test_atomic 我跑了,passed in 1.2s(输出贴附);第 2 条'失败回滚'→ test_rollback_on_partial passed in 0.4s。两条都有对应测试真过。"
  • actual_set_recorded: passed / evidence: "envelope.actual_write_set=[batch_writer.py, test_batch_write.py];git diff --name-only HEAD~1 实跑 = 这两个文件,一一对上,无 declared 外漏项。"
  • obligations_maintained: passed / evidence: "declared active_obligation 仅 no-silent-data-loss(红线);status=maintained,evidence=回滚测试覆盖了部分失败路径,无静默丢数据分支。"
  • no_unhandled_mismatch: passed / evidence: "本 task session grep MismatchDetected event = 0 条,无挂起 mismatch。"
  • git_committed: passed / evidence: "git log --oneline -1 = a1b2c3d feat(T-XX): batch atomic write,含 task_id;git status --porcelain 空,worktree clean。"

看出区别没有:✗ 不是"少查了",它五项都"查"了(都写了 passed)——它是evidence 不可证伪。我物理上不能改代码(tools 无 Edit/Write),但我若把 evidence 写成"看着对",独立性就只剩结构、没剩内容——我成了运动员请来的、闭眼鼓掌的裁判。判 passed 的资格不是"我看了 envelope",是"我真去跑/对照了物理状态、拿到了能反驳提交者的证据"。 这对示范就是我每一条 evidence 的分辨率下限。

Show full SKILL.md (305 more words)Show less

Procedure

对 envelope 逐项跑 blocking checks。check 清单的权威是 dispatch prompt 注入的那份(机器 check 注册表演化时 dispatch 先更新,本文不追数字);下面 5 项经典 check 是方法示范、不是封闭枚举——dispatch 清单里出现本文没写的 check,照同样的证据分辨率独立验,别因为文本没教就跳过:

Check 1: execution.done_criteria_satisfied

  • 对 task.done_criteria 每条,验证 actual 达成
  • 跑测试 / 验证文件存在 / verify expected behavior
  • 每条带 evidence(具体——"test_X.py::test_basic passed in 1.2s",不是"tests ok")

Check 2: execution.actual_set_recorded

  • envelope.actual_read_set / actual_write_set 是否真实反映 git diff + 读操作
  • declared 内的 entry 标 declared_in_package=true
  • declared 外的 entry 必须有 drift_reason 且具体
  • actual_read_set 4-source reconciliation:对照 capsule declared / tool access log(如有)/ executor 声明的 extra reads / 从 git diff 反推(修改 X 文件大概率读了 X 跟 caller)——v3 初版承诺: 不要求完美低层 trace,但语义相关的 extra reads 必须诚实声明(缺漏视为 actual_set_recorded failed)

Check 3: execution.obligations_maintained

  • 每条 declared active_obligation 的 status 是 maintained / violated / not_applicable
  • violated → 必须有 evidence + envelope 标到位(M-0.5 commit gate 会处理 ObligationViolated event 产出)
  • maintained → evidence 充分
  • (obligation 派生已由 projection 机器强制:active_obligations_declared 从 obligation_lifecycle_state projection 逐条派生,red_line obligation 必须全 declare——你核的是每条 status 跟 evidence 对不对得上, 谎报 maintained 会被一致性 gate 挡)

Check 4: execution.no_unhandled_mismatch

  • 本 task session 所有 MismatchDetected event 都有对应 resolution record
  • 没有"挂起的"mismatch
  • (判定 fail-closed:MismatchDetected 找不到对应 resolution record 就是 failed,不默认无事)

Check 5: execution.git_committed

  • git log 显示本 task 的 commit(含 task_id in message)
  • worktree clean state(无未 commit 改动)

输出 Structured Result(本节是镜像——权威在 dispatch prompt)

输出 schema 的权威源是 dispatch prompt 里注入的输出块(fork_prompts.py _output_schema_block), 本节只是它的镜像——两者不一致时以 dispatch 为准。 你最后一条消息【必须是且只能是】一个纯 JSON 对象:第一个字符就是 {,最后一个字符就是 },不要 markdown 围栏、不要 JSON 前后任何说明文字 (违反会被 fail-closed 判废):

json
{"self_check_result": {"passed": <bool——所有 check 全 passed 才 true>,
  "blocking_checks": [{"check_id": "...", "status": "passed|failed", "evidence": "<具体证据>"}, ...每项一条],
  "summary": "<一句话总结>"}}

passed=false 时务必在对应 check 的 evidence 写清为什么 failed(你能也应当 disprove);给主 session 的 修复建议写进 evidence / summary,别发明顶层字段。分析推理放 JSON 字段内部,不放 JSON 外。

我容易偏向哪里

走过场(橡皮图章):status=passed 但 evidence 是"looks ok"——executor 自己也写得出,我这道独立关卡白设。对治 = 把 evidence 写到上面那份 ✓ 的分辨率(可复算、能反驳提交者)。

只看 envelope 不看 actual:envelope.actual_write_set 写了某文件但 git diff 没那文件改动。 对治:每个 check 必须跟物理证据对照——不只读 envelope 字段,要跑 git diff / pytest / file exists。

升级 scope 做 review:评论"代码质量"或"设计好坏"——那是 M-1.5 的事。对治:我的 scope 只是 envelope 是否真实反映 actual + 是否完成 done_criteria,不评 quality。

真拿不准时软化或上抛:判断卡在"尺子怎么摆"(不是证据不够)时,容易软化成 conditional-pass 或 想上抛 owner。对治:调 advisor(你环境里的 advisor 工具)拿决定,照决定判——别软化、别弃权。

自检

把我每条 evidence 跟上面那份 ✓ 摆一起问:"一个零上下文 reviewer 拿这条 evidence,能不能自己复算、并据此反驳一个谎报 passed 的 executor?" 能 → ok。否 → 那条还停在 ✗ 的"看着对",补到可复算。

我不做什么

  • 不修 envelope(return checks 给主 session 修后重跑)
  • 不放过 failed checks(任一 failed → passed=false)
  • 不直接 commit
  • 不评 code quality(M-1.5 review 的事)
  • 不修代码(我的 tools 无 Edit / Write——物理上做不到,这是防自欺的结构保证)

© Towow-ai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .claude/skills/execution-self-check of Towow-ai/Flowness.

Open the folder on GitHubat commit c9d6abe

Compare with similar skills

Execution Self Check 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.

Execution Self Check compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Execution Self Check this skillTowow-ai/Flowness106—~1.8kAutomated safety check: PassApache-2.0
Inline Plan ExecutionjnMetaCode/superpowers-zh8.3k—~2.5kAutomated safety check: PassMIT
agtx Execute Phasefynnfluegge/agtx1.7k—~439Automated safety check: PassApache-2.0
Cline Pilotsickn33/agentic-awesome-skills47k1 repos~4.6kAutomated safety check: PassMIT
Requirement Ledger Workflowadand-91/gpt-6-astra-skill125—~6.3kAutomated safety check: PassMIT
Procoder Commit Gateazrtydxb/procoder211—~3.7kAutomated safety check: PassApache-2.0

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Works with

Categories

Questions about Execution Self Check

What does Execution Self Check do?

Pre-submit 自检——envelope 提交 commit gate 前必跑。独立 OPUS fork 逐项判 blocking checks(清单以 dispatch prompt 注入为准),executor 不能 self-assess(运动员不当裁判)。. Execution Self Check is an agent skill from Towow-ai/Flowness.

When should I use Execution Self Check?

Execution Self Check fits situations like: tasks that involve Verification before completion.

How do I install Execution Self Check in Claude Code?

Run `npx skills add Towow-ai/Flowness --skill execution-self-check -a claude-code`. Or copy the skill folder (.claude/skills/execution-self-check in Towow-ai/Flowness) into .claude/skills/execution-self-check in your project. Claude Code loads it when a task matches its description.

How do I install Execution Self Check in Codex?

Run `npx skills add Towow-ai/Flowness --skill execution-self-check -a codex`. Or copy the skill folder (.claude/skills/execution-self-check in Towow-ai/Flowness) into .agents/skills/execution-self-check in your project. Codex loads it when a task matches its description.

Can I use Execution Self Check 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 Towow-ai/Flowness --skill execution-self-check -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/execution-self-check, .gemini/skills/execution-self-check, .github/skills/execution-self-check and .opencode/skills/execution-self-check in your project.

What does Execution Self Check need to run?

Going by SKILL.md and its folder, Execution Self Check needs the command-line tools its instructions call (git and pytest).

Does Execution Self Check access the network?

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

Is Execution Self Check 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 Execution Self Check use?

Execution Self Check is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Execution Self Check use?

About 1.8k tokens (SKILL.md is roughly 7.1k 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 Execution Self Check?

Skills that share tags, products or a category with Execution Self Check: Inline Plan Execution (jnMetaCode/superpowers-zh, 8.3k stars), agtx Execute Phase (fynnfluegge/agtx, 1.7k stars), Cline Pilot (sickn33/agentic-awesome-skills, 47k stars) and Requirement Ledger Workflow (adand-91/gpt-6-astra-skill, 125 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Execution Self Check?

Towow-ai (a GitHub organization) maintains it in Towow-ai/Flowness, which has 106 GitHub stars. The repository holds 12 skills in this directory. The repository was last updated on August 8, 2026.

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