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/akaszubski/autonomous-dev/api-designnpx skills add akaszubski/autonomous-dev --skill api-designgit clone --depth 1 https://github.com/akaszubski/autonomous-devWrote 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/akaszubski/autonomous-dev/api-design)<a href="https://agentmods.dev/skills/akaszubski/autonomous-dev/api-design"><img src="https://agentmods.dev/badge/skills/akaszubski/autonomous-dev/api-design.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 | $0.00071 | $0.02136 |
| Opus 5 | $0.00036 | $0.01068 |
| Sonnet 5 | $0.00014 | $0.00427 |
| Haiku 4.5 | $0.00007 | $0.00214 |
Grade A, and why
api-design 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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 · 308 lines · 71 tokens per session scan A 37e4fa6309ae
api-design is a skill published in the GitHub repository akaszubski/autonomous-dev (34 stars, last pushed today), with no licence file. It adds 71 tokens to every session and 2,136 once invoked, about $0.0004 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 2026-08-30.
Other skills, from other repositories
open-draft-pr
Prepare local changes for review with an intentional commit, push, and ready PR for fallow. Use when the user wants to publish work, open a PR, or turn local changes into a reviewable branch.
browser-smoke-review
Use browser automation to review docs pages, preview URLs, rendered output, or web-facing fallow surfaces. Use when the user wants a screenshot-based review, browser smoke test, docs site check, or preview deployment inspection.
review
Perform Fallow's comprehensive pre-merge review. Use after implementation or when asked to review a branch, pull request, or diff.
address-pr-comments
Triage and address GitHub PR review feedback for fallow, then implement the agreed fixes. Use when the user wants to inspect PR comments, requested changes, or unresolved review threads and act on them.
coverage-loop
Iteratively improve Fallow Rust test coverage with cargo-llvm-cov, prioritizing meaningful untested behavior and preserving runtime correctness.
sig-audit-loop
Iteratively improve Fallow maintainability using measured SIG audit deltas, retaining only changes that improve the targeted property without regressions.