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 mgiovani/cc-arsenal --skill inject-docsgit clone --depth 1 https://github.com/mgiovani/cc-arsenalWrote 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/mgiovani/cc-arsenal/inject-docs)<a href="https://agentmods.dev/skills/mgiovani/cc-arsenal/inject-docs"><img src="https://agentmods.dev/badge/skills/mgiovani/cc-arsenal/inject-docs/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/mgiovani/cc-arsenal/inject-docs"><img src="https://agentmods.dev/badge/skills/mgiovani/cc-arsenal/inject-docs.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00143 | $0.01720 |
| Opus 5.5 | $0.00057 | $0.00688 |
| Sonnet 5.5 | $0.00029 | $0.00344 |
| Haiku 4.5 | $0.00014 | $0.00172 |
Grade C, and why
inject-docs scanned grade C with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 22d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
Requires `uv` (`curl -LsSf https://astral.sh/uv/install.sh | sh` or `brew install uv`). Run the bundled injection script using this skill's own absolute directory path, not `$(dirname "$0")`. That trick resolves against Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
Requires `uv` (`curl -LsSf https://astral.sh/uv/install.sh | sh` or `brew install uv`). Run the bundled injection script using this skill's own absolute directory path, not `$(dirname "$0")`. That trick resolves against How it starts
The opening of the file, as written. The whole thing — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Framework Documentation Injector
Inject compressed framework-specific best practices and documentation into the current project's CLAUDE.md or AGENTS.md file. This gives AI coding agents passive access to framework knowledge without requiring tool calls or skills.
Supported Frameworks
| Framework | Detection Method | Documentation Source |
|---|---|---|
| Next.js | next in package.json |
Vercel's agents-md codemod (version-aware) |
| FastAPI | fastapi in requirements.txt/pyproject.toml |
zhanymkanov/fastapi-best-practices |
Anti-hallucination guidelines
CRITICAL:
- Auto-detect the framework before running anything - check project files to identify the framework
- Do NOT assume tools are available - verify Node.js/Python tooling exists based on framework
- Do NOT claim success until verifying the target file exists and contains actual content
- Read actual output - report what the commands say, not what is expected
Implementation Workflow
Phase 0: Framework Detection & Validation (REQUIRED)
Before running anything, auto-detect the framework and verify prerequisites:
-
Detect the framework:
- Check for
package.jsonwithnextdependency → Next.js project - Check for
pyproject.tomlwithfastapidependency → FastAPI project - Check for
requirements.txtcontainingfastapi→ FastAPI project - If multiple frameworks detected, prioritize based on arguments or ask user
- If no framework detected, STOP and inform the user: "Could not detect a supported framework (Next.js or FastAPI)."
- Check for
-
Detect framework version (if applicable):
- For Next.js: extract version from
package.json - For FastAPI: extract version from
pyproject.tomlorrequirements.txt - Report the detected version to the user
- For Next.js: extract version from
-
Detect target file:
- Check if
CLAUDE.mdexists in the project root - useCLAUDE.md - Else check if
AGENTS.mdexists - useAGENTS.md - If neither exists, default to
CLAUDE.md(Claude Code's native format) - Inform the user which file will be updated
- Check if
What ships with it
4 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.
- 22d ago Changed · -1 lines scan A → C 1dc542603776
- 1mo ago Changed 0bba689d5216
- 1mo ago Changed · +1 lines da50823c7a80
- 1mo ago First seen · 161 lines · 143 tokens per session scan A c905d245b27d
inject-docs is a skill published in the GitHub repository mgiovani/cc-arsenal (8 stars, last pushed 2d ago), licensed MIT. It adds 143 tokens to every session and 1,720 once invoked, about $0.0006 per session on Opus 5.5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
basic-skill
Summarize small CSV files and identify the highest revenue month.
testing-anti-patterns
Reviews test code to identify and fix common testing anti-patterns including flaky tests, over-mocking, brittle assertions, test interdependency, and hidden test logic. Flags bad patterns, explains the specific defect, and provides corrected implementations. Use when reviewing test code, debugging intermittent or…
handoff-protocols
Manages work transitions between team members or agents by creating structured handoff documents, summarizing project status, documenting key decisions, blockers, and open questions, and generating onboarding briefs. Use when someone needs to hand off, hand over, or transition a project; pass work to another person or…
parallel-investigation
Coordinates parallel investigation threads to simultaneously explore multiple hypotheses or root causes across different system areas. Use when debugging production incidents, slow API performance, multi-system integration failures, or complex bugs where the root cause is unclear and multiple plausible theories exist…
hypothesis-testing
Applies the scientific method to debugging by helping users form specific, testable hypotheses, design targeted experiments, and systematically confirm or reject theories to find root causes. Use when a user says their code isn't working, they're getting an error, something broke, they want to troubleshoot a bug, or…
trace-and-isolate
Applies systematic tracing and isolation techniques to pinpoint exactly where a bug originates in code. Use when a bug is hard to locate, code is not working as expected, an error or crash appears with unclear cause, a regression was introduced between recent commits, or you need to narrow down which component…