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cccskills
無料GitHub で公開日本語紹介

fix-failed-paperclip-run

Paperclipの失敗・停止・遅延や誤ったブロックを調べ、原因の再現から修正、再発防止テスト、実際の利用手順の検証、チェックが通るPRの作成まで進めます。

原文原文の説明を見る

Diagnose and fix failed, stuck, slow, or incorrectly blocked Paperclip tasks and runs. Use with a task/run URL or failure report to trace the root cause, prove a regression red then green, check second-order effects, verify the real workflow, and deliver a PR with passing checks.

AI評価90点/ 100インストール方法を見る

こんなときに便利

  • Paperclipの実行失敗を直したいとき
  • 停止や誤ったブロックの原因調査
  • タスク実行の遅延を改善したいとき
  • 修正を実際の利用手順で検証

日本語での紹介

できること

Paperclipのタスクや実行が失敗する、止まる、遅い、誤ってブロックされる問題を、原因調査から修正まで扱います。タスクや実行のURL、障害報告を起点に、ログや設定、保存状態を照合します。修正前に失敗を再現するテストを用意し、修正後の成功と周辺機能への影響を確認して、必要なチェックとレビューが通るPRにまとめます。

こんなときに便利

成功表示が出たのに成果物が届かない場合や、再試行しても作業が進まない場合に向いています。コードの不具合、設定の問題、修正が利用環境に届いていない状態を見分け、証拠に応じた対応を選びます。実際の利用経路でも、成果物の保存や完了状態を確認します。

使い方の例

  • 「この実行URLから失敗原因を調べ、再現テストと修正PRを作って」
  • 「停止したタスクの原因を調べ、修正後に実際の手順で動作確認して」

注意点

調査対象への正当なアクセスと、実行環境に応じた認証情報が必要です。実環境の検証ができない場合は未検証として報告します。このスキル自体はマージやデプロイを許可しません。元のタスクの復旧まで進めるかは、与えられた権限と依頼範囲に従います。

この紹介文は、公開されている SKILL.md をもとに AI(OpenAI Codex)が作成しました。正確な仕様は下の原文を確認してください。

客観評価

SKILL.md の中身だけを根拠に、AI が 4 つの観点で判定しました。スター数や人気は判定に入れていません。

指示の明確さいつ使い、何をするかが読み取れるか
A良好失敗・停止・遅延の調査から実利用の検証とPR作成までの到達点が明記されています。
手順の具体性手順・入出力・例が具体的に書かれているか
A良好ログ照合、修正前の失敗再現、修正後の検証と副作用のテストが具体的です。
安全面送信・削除・コマンド実行などの扱いが明示されているか
A良好認証情報の秘匿、アクセス境界の順守、再試行前の保存を求め、マージ権限も限定します。
導入のしやすさ必要なツールや API キーが少ないか、書かれているか
B一部不足実行環境や認証元の確認は求めますが、必要なツールや認証の導入手順はありません。

合計点は、各項目を A=25点・B=15点・C=5点として足したものです。 2026年10月20日 時点で AI(OpenAI Codex)が判定しました。目安なので、入れる前に原文も確認してください。

評価が違うと思ったら、見直しを依頼する

どの項目が、なぜ違うと思うかを書いてください。ログインは不要です。内容を SKILL.md と照らし合わせて評価を作り直し、この欄に反映します。

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含まれるファイル(2)

  • SKILL.md12.9 KB
  • references/failure-patterns.md7.5 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Fix Failed Paperclip Run

Own the failure from evidence through a tested repair and a green PR. A diagnosis, a proposed plan, a successful provider turn, and a passing unit test are intermediate results. The finish line is a verified user workflow and a PR whose current commit passes the required checks and review.

Honor an explicit diagnosis-only request or a calling workflow's approval boundary. Otherwise proceed through implementation without a separate plan-approval pause. Carry forward existing authorization for merge, rollout, and recovery; do not ask again. When the assignment ends at a PR, distinguish local verification from deployment and recovery of the original task. This skill does not itself authorize merging or deploying.

1. Establish the incident and the finish line

Start from the supplied task/run URL or failure report. Resolve these facts from available tools and records before asking the user for missing information:

  • Instance, company, task, affected run(s), time window, and intended useful result.
  • Current state versus state at failure; parent/child tasks and pending interactions only where they control progress. Multiple failed runs can have different causes.
  • The code actually served, runner/provider pack versions, operating system and architecture, adapter, model/effort, execution workspace, trust mode, and credential source. Trace effective values back through task overrides, inherited settings, defaults, and saved session state. Redact credential values.
  • Which endpoint is authorized: verified fix and green PR, or also rollout and recovery. Preserve the requested work and success criteria throughout.

Use authorized diagnostic access. If company scoping blocks a read, use an already-authorized diagnostic path or label the missing evidence; do not bypass the boundary.

Read repository instructions and the relevant current execution contract. In this repository, use doc/execution-semantics.md for ownership, continuation, waiting, finalization, and recovery. Inspect recent changes and open/merged repairs in the affected area. A correct fix that has not reached the target is a deployment gap; do not create a second patch without evidence that the first is insufficient. Choose code repair, configuration repair, or recovery from that evidence. If an existing fix is sufficient, verify it and continue to the authorized endpoint using its PR; do not manufacture code changes for an already-fixed defect.

Keep a compact evidence record in the working notes or driving issue: environment, revision, causal timeline, reproduction, safety assumptions, and acceptance result. Preserve useful logs and saved work before retries or cleanup. Do not put secrets or private incident links in public code, fixtures, skills, or PR descriptions.

2. Find the first causal failure

Reconstruct the run from dispatch through preparation, provider execution, tool calls, result persistence, finalization, and task disposition. For chat/email work, follow outbound delivery and the user-visible result too. Align run events, logs, controller/provider records, task activity, and traces by time and identity.

Separate these questions:

  1. What first prevented useful work or its delivery?
  2. Why did the responsible component make that decision or emit that value?
  3. Why did recovery or continuation fail to complete the already-authorized work?
  4. Which later errors are consequences, misleading summaries, or independent bugs?

Trace the causal value or transition to its producer and shared contract. Verify the hypothesis against a counterexample or a reproduction. Check logs before and after the apparent error: a recovered authorization warning may not be fatal, and “final response,” HTTP 200, or “run succeeded” may not mean the task is complete. Missing error detail is an evidence gap, not proof of a provider outage. When evidence cannot distinguish hypotheses, name the uncertainty and add the smallest bounded, redacted observation or fault injection that will resolve it.

For a stalled tree, classify each relevant non-progressing node as genuinely waiting on a named human/external dependency, agent-actionable but unrouted, or already covered by existing work. Preserve all three invariants:

  • Productive work has a real next action and owner.
  • Genuine approval, credential, budget, and dependency blockers remain effective.
  • Recovery and continuation are bounded and cannot recursively recover themselves.

Consult failure patterns for matching mechanisms and test oracles. Treat them as hypotheses to check, not a catalog of explanations.

3. Prove the bug before changing production code

Write the smallest behavioral regression at the boundary that owns the defect. Run it against the unfixed code and capture the expected failure. A setup error, missing dependency, or assertion about a mock's own return value is not the red.

  • Use the real policy/resolver/serializer and realistic persisted input. Mock only boundaries outside the behavior under test. If a query duplicates rows, exercise that query with the relational shape that produces duplicates.
  • For recovery or races, control the interruption point and assert the resulting ownership, command receipts, side effects, and continuation. Restarting between completed turns does not reproduce a restart during an in-flight side effect.
  • For packaging, process startup, platform, or cross-language defects, reproduce using the actual affected artifact or protocol. A host binary or mocked provider cannot prove that a sandbox image contains an executable compatible binary.
  • For latency, measure the user's full interval and the suspected stage under the relevant cold/warm conditions. Use a stable controlled regression where possible; keep noisy wall-clock comparisons as measured acceptance evidence.

Keep this failing regression as the starting point for the repair. If the defect requires a real integration environment, capture a repeatable failing integration probe before the fix and repeat it afterward; add a durable regression at the closest reliable boundary. If no meaningful red can be observed, report that gap and keep working on reproduction. Do not claim red-green proof from a test that was first run after the fix.

4. Repair the cause and prove the safety assumptions

Fix the responsible producer or shared transition at the narrowest correct scope. Check sibling callers/adapters that share that contract; generalize only as far as the evidence requires. Avoid historical string allowlists, swallowed errors, unbounded retries, or relaxing an integrity check to accommodate malformed input. Preserve the requested model, trust, isolation, and performance behavior unless a change or explicit fallback policy is part of the assignment.

Before implementation, state the behavioral rule and the strongest plausible second-order failure. Trace callers, downstream consumers, persisted state, and runtime variants affected by the changed contract. Turn the important safety assumptions into observable regression cases, not just assurances in the PR:

Changed boundarySafety evidence to consider
Ownership, cancellation, retry, or continuationNo second executor or repeated external side effect; legitimate queued work still runs; cancellation remains effective. An unchanged assignee field alone is insufficient.
Recovery or finalizationSaved files, results, and sessions survive; known-complete work is not rerun; interrupted work continues once; indeterminate outcomes reconcile before retry.
Waiting or task dispositionReal approval/budget/credential gates still stop work; actionable work has a durable wake; recovery is bounded; no recursive recovery tree.
Input, tool, or credential plumbingCompany and trust boundaries hold; intentional configuration reaches execution without ambient secret forwarding; distinct tools still dispatch correctly; sensitive logging remains redacted.
Packaging, compatibility, or session identityRelevant local/sandbox, platform, fresh/resumed, and old/new artifact combinations work; obsolete saved values are handled by a contract rather than a list of incident exceptions.
Performance or lifecycleWarm reuse remains warm where intended; queueing and finalization do not regress; configured deadlines retain their meaning.

Select cases that exercise the actual blast radius. Do not create an unrelated platform matrix. Test the sibling success path and the negative case that the old guard protected. Keep reproduction and safety tests through later revisions.

With the red established and the safety assumptions identified, make the repair and run the same regression green. Run the relevant safety cases and existing tests. Refactor only while they stay green. Investigate unexpected failures instead of weakening an assertion or deleting the regression to finish.

Routine infrastructure facts belong to the harness when it can determine them under existing authority. Reconcile process ownership, saved results, or eligible continuations in code instead of asking a user to certify those facts in a form. Keep UI choices for genuine user intent, authorization, or unavailable information.

5. Verify the real workflow at the fixed revision

Apply the repository's verify-paperclip skill and affected map recipes when available. Its essential requirement here is a real run through the affected user entry point, using the fixed source or package and the relevant runtime configuration. Run the narrow regression first so each hypothesis gets fast feedback; use a local server with the real remote provider when that reproduces the failure. Do not wait for a full deployment for every experiment when a faithful shorter loop exists.

Exercise the original failure mechanism with a representative task: actual adapter, provider, tools, trust boundary, persisted state, artifact, and interruption point where each matters. A mock, Storybook, provider-free benchmark, or generic “hello” smoke is supporting evidence only when the incident depends on a different path.

Verify the useful output, persistence after reload/reconnect, finalization, and correct task state with no stranded lock or pending operation. For resume and conversation defects, run a second turn and check retained context/files. For delivery defects, check the destination and user-visible outcome, not just receipt of an HTTP request. For slowness, compare the end-to-end interval with the baseline.

Record the tested revision and runtime versions. Re-run affected acceptance after changes that invalidate that evidence. Report any missing credentials, access, or environment precisely; an unavailable live check remains unverified. Continue independent repair and PR work instead of substituting an unsupported “works” claim.

6. Deliver the PR and close the incident to the authorized endpoint

Use prepare-paperclip-pr and prcheckloop when available. Follow repository instructions for checks, branch isolation, PR template, and review. Open the PR, address review and CI failures, and inspect required checks and review on the current head SHA. Pending, skipped, and passing are distinct. Retry a failed check only with a reason; retain its evidence and fix repeatable failures. Resolve companion repository/artifact changes needed by the fix and state their ordering.

The PR must explain the causal defect, behavioral change, failing-before/passing- after evidence, safety regressions, actual acceptance environment, and limitations. Do not declare it ready while required checks or review remain unresolved. If a required service or permission prevents completion, name the exact remaining gate.

When rollout/recovery is already authorized, continue: confirm the served revision and required artifact versions, re-read the original task, and recover it through the normal product path. Reconcile existing work before starting another executor. Observe the original useful result or a genuine, named remaining blocker. Do not cancel, replace, or shrink the user's original task merely to make a test pass.

Finish with a concise report:

  • Root cause and what changed, with unresolved hypotheses labeled.
  • Red/green regression and second-order behavior checked.
  • Real workflow exercised, revision/environment, and observed result.
  • PR URL, current check/review status, and companion changes if any.
  • Whether the original task is recovered, still awaiting rollout, or blocked on a specific remaining dependency. Separate code readiness from incident recovery.

Do not stop at a plan when a fix is authorized. Do not call the incident resolved because its error message improved or a successful run badge appeared.

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