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 natnew/awesome-ai-scientists --skill feature-specgit clone --depth 1 https://github.com/natnew/awesome-ai-scientistsWrote 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/natnew/awesome-ai-scientists/feature-spec)<a href="https://agentmods.dev/skills/natnew/awesome-ai-scientists/feature-spec"><img src="https://agentmods.dev/badge/skills/natnew/awesome-ai-scientists/feature-spec/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/natnew/awesome-ai-scientists/feature-spec"><img src="https://agentmods.dev/badge/skills/natnew/awesome-ai-scientists/feature-spec.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 | $0.00082 | $0.00532 |
| Opus 5 | $0.00041 | $0.00266 |
| Sonnet 5 | $0.00016 | $0.00106 |
| Haiku 4.5 | $0.00008 | $0.00053 |
Grade A, and why
feature-spec 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 9d 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.
What it actually says
Feature Spec
Workflow
1. Find the next phase
Read specs/roadmap.md. The next phase is the first section whose items are all [ ]. Note its name to derive the branch and directory name.
2. Create the branch
git checkout -b phase-N-<kebab-name>
3. Interview the user — BEFORE writing any files
Use AskUserQuestion with exactly 3 questions in one call:
| Header | Question focus |
|---|---|
| Scope | What the feature collects, exposes, or does — fields, behaviour, data shape |
| Decisions | Key implementation choices — storage, visibility, validation, UX pattern |
| Context | Tone, constraints, or anything shaping the spec — copy style, stack limits, open questions |
Do not write any files until the user has answered all three questions.
4. Read guidance files
Read specs/mission.md and specs/tech-stack.md before drafting.
5. Create the spec directory
Name: specs/YYYY-MM-DD-<feature-name>/ using today's date.
requirements.md
- Scope section: what is and is not included; field/data table if applicable
- Decisions section: choices made and why (draw from user answers)
- Context section: tone rules, stack pointers, existing patterns to follow
plan.md
- Numbered task groups appropriate to the feature (for example: Data → Components → Page & Route → Navigation → Tests)
- Each group has numbered sub-tasks; groups should be independently implementable
validation.md
- Automated: project test and typecheck commands pass; specific assertions required
- Manual: walkthrough, behaviour, edge cases
- Tone check if the feature has user-facing copy
- Definition of done
Constraints
- Respect the existing tech stack defined in
specs/tech-stack.md— no new dependencies without user approval - Follow existing conventions and patterns already established in the codebase
- Keep feature scope focused and independently shippable
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.
- 9d ago First seen · 60 lines · 82 tokens per session scan A a1a97378945d
feature-spec is a skill published in the GitHub repository natnew/awesome-ai-scientists (18 stars, last pushed 1mo ago), licensed MIT. It adds 82 tokens to every session and 532 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
run-work
Execute a work unit end-to-end: sequence tasks by dependency, implement, test between tasks, commit, and track progress. Use to deliver a complete feature in one session. Invoked as /agiflow:run-work . Uses getworkunit, listtasks, updatetask, getworkunitprogress.
writing-modpack-changelog
Use when cutting a modpack release. Creates /docs/release-changelog.md if absent; appends a new version section with grouped changes. Triggers - 'cut a release', 'release notes', 'changelog', 'v1.2.3 changes', 'what changed since last version'.
git-worktree-isolation
A Git workflow that gives each development task its own worktree, which is a separate working directory linked to a branch. It keeps parallel tasks and experiments apart from the main checkout.
review-prs
Triage open PRs — screen from the diff, delegate the admission judgment to audit-the-list, then merge or close on GitHub. Fire when the maintainer asks to review PRs, process the PR queue, or judge whether a specific PR should be merged.
sprr
Single PR reviewer for awesome-quant. Use when the user asks to review, validate, comment on, label, close, or merge one specific pull request that adds README.md entries. Triggers include "sprr", "review PR", "check PR", and "validate contribution".
bprr
Bulk PR reviewer for awesome-quant. Use when the user asks to review all open PRs, review unreviewed PRs, bulk review, or mentions "bprr". Reviews open PRs lacking the reviewed label and presents a summary before any merge/comment/label action.