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 jrobelia/inventree-plugin-ai-toolkit --skill implementgit clone --depth 1 https://github.com/jrobelia/inventree-plugin-ai-toolkitWrote 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/jrobelia/inventree-plugin-ai-toolkit/implement)<a href="https://agentmods.dev/skills/jrobelia/inventree-plugin-ai-toolkit/implement"><img src="https://agentmods.dev/badge/skills/jrobelia/inventree-plugin-ai-toolkit/implement/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/jrobelia/inventree-plugin-ai-toolkit/implement"><img src="https://agentmods.dev/badge/skills/jrobelia/inventree-plugin-ai-toolkit/implement.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 | $0.00016 | $0.00097 |
| Opus 5.5 | $0.00006 | $0.00039 |
| Sonnet 5.5 | $0.00003 | $0.00019 |
| Haiku 4.5 | $0.00002 | $0.00010 |
Grade A, and why
implement 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 1mo 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.
This is a copy
100% identical to implement — 6 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Implement the work described by the user in the spec or tickets.
Use /tdd where possible, at pre-agreed seams.
Run typechecking regularly, single test files regularly, and the full test suite once at the end.
Once done, use /code-review to review the work.
Commit your work to the current branch.
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.
- 1mo ago First seen · 16 lines · 16 tokens per session scan A 6d3fd9e83b8f
implement is a skill published in the GitHub repository jrobelia/inventree-plugin-ai-toolkit (1 stars, last pushed 26d ago), licensed MIT. It adds 16 tokens to every session and 97 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to implement, differing in 6 lines, and is treated as a copy.
Other skills, from other repositories
implementation-phase
Executes implementation tasks using Test-Driven Development, prevents code duplication through anti-duplication checks, and maintains quality through continuous testing. Use when implementing features from tasks.md, during the /implement phase, or when the user requests TDD-based implementation. (project).
team-qa
Orchestrate the QA team through a full testing cycle — qa-lead strategy and test plan, qa-tester case writing, execution, sign-off.
conductor-implement
Execute tasks from a track's implementation plan following TDD workflow.
gh-issue
Size-audit, write, and split BanyanDB issues that somebody else or an automated TDD workflow can implement. Use whenever the user asks to file or revise an issue, decide whether an issue is too large, make an issue TDD-ready, turn a design into tickets, or split an umbrella into executable leaves. Do not draft or file…
implement-feature
Implement an approved feature plan with fresh-context slices, TDD, revision-bound evidence, and PR-ready output.
product
Consolidated Galyarder Framework Product intelligence bundle.