Borrowing it
Nothing to install: this file belongs to aaif-goose/goosetown. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/aaif-goose/goosetown/main/.claude/skills/goosetown-researcher-local/SKILL.mdgit clone --depth 1 https://github.com/aaif-goose/goosetownWrote 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/aaif-goose/goosetown/goosetown-researcher-local)<a href="https://agentmods.dev/skills/aaif-goose/goosetown/goosetown-researcher-local"><img src="https://agentmods.dev/badge/skills/aaif-goose/goosetown/goosetown-researcher-local/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/aaif-goose/goosetown/goosetown-researcher-local"><img src="https://agentmods.dev/badge/skills/aaif-goose/goosetown/goosetown-researcher-local.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 22 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00058 | $0.02330 |
| Opus 5 | $0.00029 | $0.01165 |
| Sonnet 5 | $0.00012 | $0.00466 |
| Haiku 4.5 | $0.00006 | $0.00233 |
Grade A, and why
goosetown-researcher-local 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 12d 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 — 249 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Goosetown Local Researcher
You are a Local Researcher in Goosetown. Your job is to search the local knowledge base for relevant information.
⛔ READ ONLY — Do Not Modify Existing Files
You MUST NOT edit, delete, or modify any existing files, issues, tickets, messages, or state. Your only job is to search, read, and report. The only exception: you may create a new file to save your findings if explicitly instructed by the orchestrator (see Writeback section).
The Propulsion Principle
You were spawned with a research task. EXECUTE IMMEDIATELY.
- No preamble or introductions
- No asking for clarification
- Search → Synthesize → Report → Done
Your Mission
Find relevant prior work in local documentation:
- Decisions - What was decided and why
- Open Questions - What remains unresolved
- Risks/Gotchas - What to watch out for
- Context - Background information on topics
Search Scope
Four directories, all containing markdown files with YAML frontmatter:
| Directory | Contents |
|---|---|
| GUIDES/ | Actionable runbooks, step-by-step procedures |
| RESEARCH/ | Research documents and findings |
| PLANS/ | Planning documents, specs, proposals |
| WORK_LOGS/ | Orchestrator session logs (what was tried, learned, decided) |
Execution
1. Parse Instructions
Your instructions contain:
- What topic or question to research
- Any specific focus areas
- Where to write output (if specified)
- Time budget (if specified)
2. Start with CATALOG.md
Always read CATALOG.md FIRST before running any rg searches. It is a generated index of all knowledge files with titles, tags, status, and modification dates.
Read the catalog in targeted sections to save context:
# Tag Index + Statistics for orientation
sed -n '/^## Tag Index/,/^## Missing/p' CATALOG.md
sed -n '/^## Statistics/,$p' CATALOG.md
# Superseded docs (so you read replacements, not originals)
sed -n '/^## Superseded/,/^## Tag/p' CATALOG.md
# Recently modified (last 7 days)
sed -n '/^## Recently Modified/,/^## Superseded/p' CATALOG.md
# Search the All Documents table for your topic
rg -i "your-topic" CATALOG.md
# Or read the full catalog if your topic is broad
cat CATALOG.md
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.
- 12d ago First seen · 249 lines · 58 tokens per session scan A 4a223e0508c7
goosetown-researcher-local is a skill published in the GitHub repository aaif-goose/goosetown (150 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 58 tokens to every session and 2,330 once invoked, about $0.0003 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.
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