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/archive228/loopkit/suggest-next-featuresnpx skills add Archive228/loopkit --skill suggest-next-featuresgit clone --depth 1 https://github.com/Archive228/loopkitWhat 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 | $0.00034 | $0.01065 |
| Opus 5 | $0.00017 | $0.00532 |
| Sonnet 5 | $0.00007 | $0.00213 |
| Haiku 4.5 | $0.00003 | $0.00106 |
Grade A, and why
suggest-next-features 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 2d 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 — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
suggest-next-features
The ledger runs dry. Either every feature_list.json entry has passes: true, or the last few sessions have been shuffling half-features and adding no new work because the spec grew and the list did not.
This skill drafts candidate additions — but to a separate file, feature_list.suggestions.json. feature_list.json is immutable except for the single passes: false → true flip that [[feature-list-json]] permits. Silently appending entries would break that contract and let a runaway session invent its own scope.
The suggestions file is a proposal. A human hand-merges chosen entries into feature_list.json; the rest are ignored or deleted. No agent, ever, edits feature_list.json directly from this skill.
Trigger
Apply when either condition holds:
jq '[.[] | select(.passes==false)] | length' feature_list.jsonreturns0.- The last 3 progress entries in
claude-progress.txtshow no newpasses: trueflips AND the user has referenced behavior not present infeature_list.json.
Do not apply just because the list looks short. 30 unfinished entries is not a trigger; 0 is.
Procedure
git log --pretty=format:'%h %s' "$(git log --grep='chore: initial scaffold' --format=%H | tail -1)"..HEAD— every commit since the scaffold. This is what actually shipped, not what was claimed.- Read the last 3 "What's done" / "Notes for the next session" entries from
claude-progress.txt. This is where recent scope creep leaks. - Read
feature_list.jsonin full. You need to know what is already enumerated so you do not propose duplicates. - Compare (1)+(2) against (3). Look for:
- Behavior the user asked for in recent sessions that has no matching entry.
- Natural next steps implied by shipped features (a feature ships a POST endpoint but no list view for its results).
- Categories the initial list under-covered (error states, empty states, mobile layout, keyboard shortcuts, offline behavior).
- Draft 5–10 candidate entries in the same shape as
feature_list.json. Every one startspasses: false. Order them roughly by priority. - Write the array to
feature_list.suggestions.jsonat the project root. Overwrite any prior draft — this file is regenerable, not append-only. - Print a one-line summary per suggestion so the operator can scan without opening the file.
- Stop. Do not touch
feature_list.json. Do not commitfeature_list.suggestions.json(it is a proposal, not project state).
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.
- 2d ago First seen · 72 lines · 34 tokens per session scan A 24d3ec232753
suggest-next-features is a skill published in the GitHub repository Archive228/loopkit (753 stars, last pushed 1mo ago), licensed MIT. It adds 34 tokens to every session and 1,065 once invoked, about $0.0002 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
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
babysit-pr
Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…
imagegen
Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…