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 davistroy/claude-marketplace --skill primegit clone --depth 1 https://github.com/davistroy/claude-marketplaceWrote 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/davistroy/claude-marketplace/prime)<a href="https://agentmods.dev/skills/davistroy/claude-marketplace/prime"><img src="https://agentmods.dev/badge/skills/davistroy/claude-marketplace/prime/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/davistroy/claude-marketplace/prime"><img src="https://agentmods.dev/badge/skills/davistroy/claude-marketplace/prime.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 | $0.00063 | $0.03554 |
| Opus 5 | $0.00032 | $0.01777 |
| Sonnet 5 | $0.00013 | $0.00711 |
| Haiku 4.5 | $0.00006 | $0.00355 |
Grade A, and why
prime 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 7d 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 — 357 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prime
Perform a comprehensive evaluation of the current codebase/project and produce a structured report covering what the project is, where it stands, and what should happen next. This is the skill to use when encountering any project for the first time, resuming work after a break, or needing a full situational assessment before making decisions.
This skill is read-only. It NEVER modifies files, commits, or pushes.
Input
Arguments: $ARGUMENTS
Optional arguments:
- A specific focus area (e.g., "testing", "deployment readiness", "documentation")
- A path to a subdirectory to scope the analysis
If no arguments are provided, evaluate the entire project from the repository root.
Instructions
Execute ALL phases below using per-phase dispatch: Phases 1, 3, and 5 run via context: fork + agent: Explore (read-only analysis, isolated context). Dispatch all three simultaneously using the Agent tool — do NOT wait for one to finish before spawning the next. They are mutually independent; only Phase 6 needs their combined output. Phase 0 (lab notebook) and Phase 6 (recommendations) run inline in the main conversation — they require full prior-phase output visibility. Phase 2 runs its git commands itself (see that phase's note).
Phase 0: Lab Notebook (Mandatory First Read)
Before any other analysis, check for LAB_NOTEBOOK.md at the repository root (and within the scoped path if $ARGUMENTS specifies a subdirectory). If it exists, read it in full before proceeding to Phase 1.
The lab notebook typically contains the most current and authoritative context for the project — active decisions, open action items, recent experiment results, and current baselines — and often contradicts or supersedes what the README claims. Reading it first prevents Phase 1-5 from producing conclusions that the lab notebook has already invalidated.
Carry forward for use throughout the remaining phases:
- Decision Log entries — inform architecture, risk, and recommendation sections
- Open Action Items — feed into open work detection and recommended next steps
- Recent experiment entries (last 3-5) — reveal what was tried, what worked, what failed
- Current Baseline measurements — use these over README descriptions when they conflict
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.
- 7d ago First seen · 357 lines · 63 tokens per session scan A 24cb96e15c43
prime is a skill published in the GitHub repository davistroy/claude-marketplace (5 stars, last pushed 3d ago), licensed MIT. It adds 63 tokens to every session and 3,554 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 2026-09-04.
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