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/noahlz/claude-plugins/zero-shotnpx skills add noahlz/claude-plugins --skill zero-shotgit clone --depth 1 https://github.com/noahlz/claude-pluginsWrote 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/noahlz/claude-plugins/zero-shot)<a href="https://agentmods.dev/skills/noahlz/claude-plugins/zero-shot"><img src="https://agentmods.dev/badge/skills/noahlz/claude-plugins/zero-shot.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 | $0.00042 | $0.00772 |
| Opus 5 | $0.00021 | $0.00386 |
| Sonnet 5 | $0.00008 | $0.00154 |
| Haiku 4.5 | $0.00004 | $0.00077 |
Grade A, and why
zero-shot 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 4d 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 — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
1. Resolve Mode and Target
- Default to dry-run. Use apply mode only if the user asks to change the file.
- Identify target: attached file, pasted markdown, file path, or skill/agent name.
- If target is missing or ambiguous, ask via
AskUserQuestion.
2. Classify
Read file, record word count, then pick classification:
| Classification | Triggers | Output |
|---|---|---|
| skill | Single-concept SKILL.md or agent without numbered steps |
1–3 imperative sentences (body only) |
| procedural | SKILL.md or agent with numbered checklist or ## N. headers |
Numbered list, 1–3 sentences per step |
| instruction | CLAUDE.md, references/**, rules/**, any non-sequential multi-## doc |
Imperative bullets per ## section |
Precedence:
- Common-knowledge override → skill (jokes, greetings, basic formatting, well-known algorithms).
- Numbered checklist or
## N.headers → procedural. - 2+
##sections, non-sequential → instruction. - Default → skill.
3. Distill
Aggression: trust LLM priors — never restate well-known formats, algorithms, etiquette, or structure the imperative already implies. Delete-test every sentence: if removal doesn't break the task, drop it. Draft, then cut again — first drafts always under-cut.
Reduction targets (min): common-knowledge ≥95%, skill ≥85%, procedural ≥75%, instruction ≥60%. If draft misses, identify under-performing clauses and cut before reporting.
Write in imperative voice. One verb per bullet, no qualifiers.
Cut:
- Framing (
Overview,Background,Introduction), result descriptions, H1s restating the filename. - Examples, rationale, illustrative code, redundant "should not" clauses.
- Format restatement after naming the format.
- Audience qualifiers redundant with
clean/safe. - Error-fallback clauses for common-knowledge tasks — the LLM handles failure.
- Negation pairs where one implies the other.
- Layout instructions implied by a count.
- "Output only X" wrappers when the imperative already scopes the response.
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.
- 4d ago First seen · 70 lines · 42 tokens per session scan A 2e91661e0dc1
zero-shot is a skill published in the GitHub repository noahlz/claude-plugins (5 stars, last pushed 2d ago), licensed MIT. It adds 42 tokens to every session and 772 once invoked, about $0.0002 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…