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/corridortech/posecap/ad-level-upnpx skills add CorridorTech/PoseCap --skill ad-level-upgit clone --depth 1 https://github.com/CorridorTech/PoseCapWhat 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 | $0.00264 | $0.02096 |
| Opus 5 | $0.00132 | $0.01048 |
| Sonnet 5 | $0.00053 | $0.00419 |
| Haiku 4.5 | $0.00026 | $0.00210 |
Grade A, and why
ad-level-up 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 2d 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mechanical shape:
THIS SESSION:
1. State the candidate + its citation (or stop — not grounded).
2. Trace it to a root cause.
3. Run the four anti-overfitting gates (all must pass) + the effectiveness pass.
4. Place it deterministically; draft the minimal edit (do NOT write yet).
5. Adversarial multi-lens review of the candidate (already-covered / coherence / placement).
6. PRESENT the proposal + rationale. Apply ONLY on explicit approval, one item at a time.
The whole point is that a full or drifting context never edits the rules unsupervised — so the write is always downstream of an explicit human OK.
<background_information>
The companion that evolves the rule-set ad-audit audits against. Curation is a WRITE operation behind a human gate — distinct from the read-only ad-audit. The mechanism (four anti-overfitting gates, effectiveness pass, deterministic placement, adversarial multi-lens review, hard human gate) is ADR-0037; the rule-set locations are ADR-0035 (machine store) and ADR-0043 (project layer at .agentic/rules/, committed or machine-local via .git/info/exclude — a project rule shadows a conflicting machine-store rule, and the audit reports the shadowing). On Claude Code the multi-lens review fans out Task subagents; on Codex it runs inline with an optional user-initiated rule-candidate-reviewer escalation. The skill owns the terse rule-set only — bigger decisions route to ad-adr / ad-guidelines.
</background_information>
Running ad-level-up (Codex single-pass, human-gated). I will state the candidate + evidence, trace its root cause, run the four anti-overfitting gates + effectiveness pass, place it, draft the minimal edit, run an adversarial multi-lens review, then PRESENT a proposal. I will NOT write anything to the rule-set until you explicitly approve — one item at a time.
Step 1 — state candidate + evidence. One sentence + the citation (finding / PR / transcript / file:line, or the ad-audit handoff). If it cannot be cited, stop — not grounded.
Step 2 — trace to root cause. Attach the candidate to the upstream cause (investigation / grounding / verification gap), not the surface symptom.
Step 3 — four anti-overfitting gates. All must pass; reject the rest out loud: (a) recurrence or deliberate decision; (b) generalisation (a class of future work); (c) load-bearing root cause; (d) proportionate cost (earns its keep against adherence decay).
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago First seen · 83 lines · 264 tokens per session scan A e25898481648
ad-level-up is a skill published in the GitHub repository CorridorTech/PoseCap (190 stars, last pushed 10d ago), licensed Apache-2.0. It adds 264 tokens to every session and 2,096 once invoked, about $0.0013 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 2026-08-30.
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…