Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/ohong/agent-skills/validatenpx skills add ohong/agent-skills --skill validategit clone --depth 1 https://github.com/ohong/agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ohong/agent-skills/validate)<a href="https://agentmods.dev/skills/ohong/agent-skills/validate"><img src="https://agentmods.dev/badge/skills/ohong/agent-skills/validate.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00029 | $0.00563 |
| Opus 5 | $0.00015 | $0.00282 |
| Sonnet 5 | $0.00006 | $0.00113 |
| Haiku 4.5 | $0.00003 | $0.00056 |
Grade A, and why
validate scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mission Validate — Let Reality Speak
Every action is a hypothesis test. Validation is how reality answers.
Run acceptance criteria without advancing. Use to check your work, verify after a fix, or confirm the full mission is healthy. This is pure Observation — the most honest phase of the OODA cycle.
Target: $ARGUMENTS
Procedure
-
Read
.mission/plan.mdand.mission/progress.md. -
Determine scope:
$ARGUMENTSis a number → validate that specific milestone$ARGUMENTSis "all" → validate ALL milestones (full sweep)$ARGUMENTSis empty → validate the current milestone (first incomplete)
-
For each milestone, run every acceptance criterion from the plan.
-
Report:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
VALIDATION: Milestone {N}: {title}
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
✅ `bun test` — passed (12 tests, 0 failures)
✅ `bun run build` — passed
❌ `bun run typecheck` — FAILED
→ src/api/users.ts:42 — Type 'string' not assignable to 'number'
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Result: 2/3 passed, 1 FAILED
- For "all" validation, show a summary:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
FULL VALIDATION SWEEP
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
✅ Milestone 1: Set up schema — all pass
✅ Milestone 2: API routes — all pass
❌ Milestone 3: Frontend — 1/3 failed
⬜ Milestone 4: Integration — not yet implemented
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
- Suggest next action:
- All pass → "Validation clean. Continue with
/mission:continue." - Failures → "Mismatches detected. Fix the failures, then re-run
/mission:validate."
- All pass → "Validation clean. Continue with
Rules
- Run commands, don't inspect. Validation means executing commands, not reading code and deciding it "looks right." Self-assessment is the enemy of truth.
- Report precisely. Include exact error output. This is observation data for whoever acts on it next.
- Don't fix anything. This is observation, not action. Fixing happens in
/mission:startor/mission:continue.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 67 lines · 29 tokens per session scan A d055c8091cd1
validate is a skill published in the GitHub repository ohong/agent-skills (2 stars, last pushed 3d ago), licensed MIT. It adds 29 tokens to every session and 563 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…