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 skills add PANYUXIN6/pyx-skills --skill repo-map-firstgit clone --depth 1 https://github.com/PANYUXIN6/pyx-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/panyuxin6/pyx-skills/repo-map-first)<a href="https://agentmods.dev/skills/panyuxin6/pyx-skills/repo-map-first"><img src="https://agentmods.dev/badge/skills/panyuxin6/pyx-skills/repo-map-first/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/panyuxin6/pyx-skills/repo-map-first"><img src="https://agentmods.dev/badge/skills/panyuxin6/pyx-skills/repo-map-first.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 5.1 | $0.00065 | $0.01585 |
| Opus 5 | $0.00032 | $0.00792 |
| Sonnet 5 | $0.00013 | $0.00317 |
| Haiku 4.5 | $0.00006 | $0.00159 |
Grade A, and why
repo-map-first 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 5d 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 — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Place Changes with Repository Evidence
Resolve where a change belongs before implementing it when placement mistakes could cross responsibilities or spread through the wrong layer. Keep repository maps evidence-based and update them only when the task or an explicit request justifies the documentation work.
Select the Invocation Mode
Explicit Map Mode
Use this mode whenever the user names this skill or asks to create, repair, update, inspect, or use repository map documents.
The requested action determines the scope; naming the skill does not itself authorize document changes.
- Inspect or use: read relevant existing maps, verify task-relevant claims against source, and report ownership, discrepancies, and limitations. Resolve missing information from source when possible. Missing or stale maps do not turn inspection into a creation or repair task.
- Create, repair, or update: inspect existing maps and source, then create missing documents or repair stale relevant sections within the requested scope. When the user requests repository maps without naming documents, cover both
docs/REPO_MAP.mdanddocs/ARCHITECTURE.md; a request for one document does not require creating its companion. Leave accurate sections unchanged. - Complete the requested map work before any dependent implementation. A map-only request ends with the map result and its evidence; it does not authorize code changes.
Map work is sufficient when the requested owners, entry points, flows, and dependencies are locatable and evidence-backed, with material unknowns explicit. Inspection may report an unresolved gap without modifying documents. Creation and repair must produce the requested artifacts or explain which missing evidence prevents that.
Automatic Placement-Risk Mode
Use this mode only when an existing-repository behavior change has a real placement risk, such as:
- responsibility ownership or the implementation location remains unclear from the request and known context;
- the change crosses module or layer boundaries;
- entry points, dependency direction, public contracts, or key call flows may change;
- the repository is unfamiliar and the work is non-local;
- a relevant map appears missing, stale, contradictory, or insufficient for a cross-boundary decision.
What ships with it
3 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.
- 5d ago Changed · -1 lines · -21 tokens per session 75b5bdf0a4fc
- 11d ago First seen · 121 lines · 86 tokens per session scan A 59eecd445c6a
repo-map-first is a skill published in the GitHub repository PANYUXIN6/pyx-skills (6 stars, last pushed 5d ago), licensed MIT. It adds 65 tokens to every session and 1,585 once invoked, about $0.0003 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.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…