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/cintia09/codenook/skill-resolvenpx skills add cintia09/CodeNook --skill skill-resolvegit clone --depth 1 https://github.com/cintia09/CodeNookWrote 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/cintia09/codenook/skill-resolve)<a href="https://agentmods.dev/skills/cintia09/codenook/skill-resolve"><img src="https://agentmods.dev/badge/skills/cintia09/codenook/skill-resolve.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 | $0.00000 | $0.00377 |
| Opus 5 | $0.00000 | $0.00188 |
| Sonnet 5 | $0.00000 | $0.00075 |
| Haiku 4.5 | $0.00000 | $0.00038 |
Grade A, and why
skill-resolve 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.
What it actually says
skill-resolve (builtin skill)
Role
Resolve a skill name against the 4-tier lookup chain so sub-agents self-bootstrap deterministically. Implements implementation.md §M5.5.
Lookup order
- plugin_local —
<ws>/.codenook/memory/<plugin>/skills/<name>/SKILL.md - plugin_shipped —
<ws>/.codenook/plugins/<plugin>/skills/<name>/SKILL.md - workspace_custom —
<ws>/.codenook/skills/custom/<name>/SKILL.md - builtin —
<core_dir>/skills/builtin/<name>/SKILL.md
Where <core_dir> comes from the CODENOOK_CORE_DIR environment
variable, falling back to the directory containing resolve-skill.sh's
skills/builtin ancestor.
CLI
resolve-skill.sh --name <skill> --plugin <plugin> --workspace <ws> [--json]
Output is always JSON (the --json flag is accepted for symmetry; default
is JSON anyway).
Output
Found:
{ "found": true, "name": "...", "path": "...", "tier": "plugin_local" }
Not found (exit 1):
{ "found": false, "name": "...", "candidates": [ "...", "...", "...", "..." ] }
Safety
--nameis rejected if it contains/,.., or any character outside[A-Za-z0-9._-]. Exit code 2 (usage).- Each candidate path is resolved + a containment check ensures it sits under the workspace OR the core directory before being returned.
What ships with it
2 files 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.
- 3d ago First seen · 46 lines · 0 tokens per session scan A 3978d80e07a3
skill-resolve is a skill published in the GitHub repository cintia09/CodeNook (5 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 377 tokens. 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
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brainstorming
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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…