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Skill1.9k estrellas del repoactualizado 5d ago

ha-debug

Hope-native debugging for code failures, regressions, crashes, flaky behavior, and bad output: reproduce or characterize, rank falsifiable hypotheses, fix the smallest root cause, and prove the failing path.

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SKILL.md

# Hope Debug

Debug from evidence, not from the first plausible explanation. This is a
decision process, not a mandatory four-stage ceremony.

## 1. Characterize The Failure

Capture the strongest available evidence:

- Exact symptom, expected behavior, and observed behavior.
- Reproduction steps, failing command, stack trace, log range, or persisted
  state.
- Whether it is deterministic, intermittent, platform-specific, data-specific,
  or timing-sensitive.
- Recent relevant diffs, dependency/config changes, and known-good boundary.

If reproduction is unsafe or requires unavailable credentials, characterize it
from logs, fixtures, state, and code paths. State the evidence gap explicitly.

## 2. Bound The Fault

Trace the smallest credible path through inputs, state transitions, persistence,
concurrency boundaries, and outputs. For multi-component systems, compare what
crosses each boundary rather than adding broad instrumentation everywhere.

Common high-value checks:

- Stale or duplicated persisted state.
- Error swallowing, fallback, retry, cancellation, and timeout paths.
- Async ordering, locks, process boundaries, and late results.
- Platform, locale, permission, path, and environment assumptions.
- Mismatch between source-of-truth data and UI projection.

## 3. Rank Falsifiable Hypotheses

Keep one or two active hypotheses. For each, write:

- Why it explains the evidence.
- What observation would disprove it.
- The cheapest discriminating check.

Run the discriminating check before editing when practical. If a tiny, obvious
fix is itself the cheapest safe experiment, keep it reversible and inspect the
result before broadening scope.

## 4. Fix The Root Cause

- Patch the smallest ownership boundary that restores the contract.
- Avoid subsystem rewrites before the fault is proven.
- Preserve unrelated user work and existing public behavior.
- Add defense-in-depth only when it covers a demonstrated adjacent failure, not
  as speculative cleanup.

After two failed fix attempts, stop patching variants. Re-read the original
evidence, challenge the shared assumption, and narrow the boundary again.

## 5. Prove The Failing Path

Use `ha-test-strategy` to choose the regression form and `ha-verify` to confirm
completion. Prefer a check that would have failed before the fix:

- Focused automated regression test.
- Existing failing command or deterministic fixture.
- Before/after database or log query.
- Manual reproduction when automation is not credible.

Passing compilation alone does not prove a runtime bug fixed. If the real path
cannot be exercised, report the strongest substitute and remaining uncertainty.

## Stop Conditions

Pause and ask for input only when progress requires inaccessible user state, an
external system change, destructive action, or a product decision. Do not invent
data or mark an unreproduced hypothesis as confirmed.

## Smoke Prompts

- "This test fails intermittently; find and fix the root cause."
- "The UI shows stale state after restart; diagnose the persistence path."
- "Use this session id and logs to explain the regression, then repair it."
code-reviewSkill

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email-draftSkill

Use when the user asks to draft, polish, translate, or reply to an email. Produces a clean draft with subject line, greeting, body, and sign-off, plus a pre-send self-check.

feishuSkill

Use when the user mentions 飞书 / Feishu / Lark workspace operations: docx (云文档) read/write, bitable (多维表格) records / views / dashboards, drive (云盘) upload/download, wiki (知识库) link resolution, approval (审批) instance create/cancel/query, calendar (日历) event create/list/update + attendees, contact (联系人) user/department lookup, hire (招聘) job/talent/application listing. Trigger on phrases like 'OKR 周报', '把这份文档发到飞书云盘', '给团队拉个评审会议', '查 [姓名] 的联系方式', '撤销那条审批', '/wiki 链接', or any request that mentions a feishu / lark URL / token (doxcn.../bascn.../wikcn.../boxcn.../om_...).

ha-browserSkill

Hope Agent browser automation — the standard `status → tabs → snapshot → act` loop, stale-ref recovery rules, and what to do when login / 2FA / captcha / camera-prompt / dialog blocks progress. Load this skill whenever you reach for the `browser` tool. Trigger on: user asks the agent to open / control / click / scrape / log into / verify something in a web app ('open X and click Y', '打开 X 然后点击 Y', 'log into my Gmail', 'scrape this page', 'fill out the form on X'); user reports a flow that requires real browser context (cookies, JS-rendered content, OAuth).

ha-code-reviewSkill

Hope-native review of uncommitted, staged, commit, branch, or PR changes: discover concrete regressions, independently verify candidates, and report actionable findings first without speculative noise.

ha-coding-commonSkill

Hope-native baseline for implementing, fixing, refactoring, and maintaining code: inspect the repository first, protect user changes, keep scope narrow, and finish with direct evidence.

ha-coding-planSkill

Hope-native implementation planning for non-trivial code changes: ground the plan in repository evidence, order dependencies, name critical files and risks, define verification, then continue execution when allowed.

ha-data-analyticsSkill

Hope-native local-first data analysis and Artifact reporting. Use for CSV/XLSX analysis, KPI readouts, metric diagnosis, product/business analysis, data-quality review, dashboards, charts, analytical reports, 数据分析, 指标诊断, 数据质量, 分析报告, or when the user wants a shareable offline HTML/ZIP/Markdown/PDF result. Produces the versioned AnalysisArtifactV1 contract and registers it with the artifact tool; never guesses missing data or requires public web deployment.