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 Nano-Nimbus/locus --skill locus-feedbackgit clone --depth 1 https://github.com/Nano-Nimbus/locusWrote 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/nano-nimbus/locus/locus-feedback)<a href="https://agentmods.dev/skills/nano-nimbus/locus/locus-feedback"><img src="https://agentmods.dev/badge/skills/nano-nimbus/locus/locus-feedback/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/nano-nimbus/locus/locus-feedback"><img src="https://agentmods.dev/badge/skills/nano-nimbus/locus/locus-feedback.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 | $0.00060 | $0.00763 |
| Opus 5.5 | $0.00024 | $0.00305 |
| Sonnet 5.5 | $0.00012 | $0.00153 |
| Haiku 4.5 | $0.00006 | $0.00076 |
Grade A, and why
locus-feedback 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.
How it starts
The opening of the file, as written. The whole thing — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Locus Feedback
Record quality feedback on the most recent Locus run. Annotates the run's metrics file with a user verdict so retrieval quality can be tracked over time.
Usage: /locus-feedback <quality> [note]
Arguments:
quality(required) —pass,partial, orfail(aliases:good/ok/bad)note(optional) — free-text explanation (quote if it contains spaces)
Examples:
/locus-feedback pass
/locus-feedback partial "Got the right room but missed the port number"
/locus-feedback fail "Answered about the wrong service entirely"
Steps
1. Resolve quality value
Map the first argument to a canonical value:
passorgood→"pass"partialorok→"partial"failorbad→"fail"
If the argument is missing or unrecognized, stop and output:
Usage: /locus-feedback <pass|partial|fail> [note]
2. Find the palace root
Walk up from the current working directory looking for a directory that contains
both INDEX.md and _metrics/. Stop at the filesystem root if not found.
If no palace root is found, output:
Error: no palace found (no _metrics/ directory above current path).
Run from inside a palace directory.
3. Find the most recent metrics file
List all .json files in <palace_root>/_metrics/ sorted by modification time
(most recent first). Use the first result.
If _metrics/ is empty or missing:
Error: no metrics files found in <palace_root>/_metrics/.
Run a locus query first to generate a metrics file.
4. Read and validate the metrics file
Read the file. Parse as JSON. Check:
schema_versionis"1"— if not, warn but continuefeedbackfield isnull— if already set, output a warning:
Then overwrite.Warning: this run already has feedback (<existing quality>). Overwrite? If yes, re-run with the same command. (Proceeding to overwrite.)
5. Write feedback
Set the feedback field to:
{
"quality": "<resolved quality>",
"note": "<note or null>",
"recorded_at": "<current UTC timestamp in ISO 8601>"
}
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 Changed · +9 lines · +60 tokens per session 16c44ec1fea5
- 1mo ago First seen · 103 lines · 0 tokens per session scan A e023c7acb363
locus-feedback is a skill published in the GitHub repository Nano-Nimbus/locus (0 stars, last pushed 1mo ago), licensed MIT. It adds 60 tokens to every session and 763 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-31.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
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…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
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…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…