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 Studio-Moser/Shelby-MCP --skill shelby-foragegit clone --depth 1 https://github.com/Studio-Moser/Shelby-MCPWrote 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/studio-moser/shelby-mcp/shelby-forage)<a href="https://agentmods.dev/skills/studio-moser/shelby-mcp/shelby-forage"><img src="https://agentmods.dev/badge/skills/studio-moser/shelby-mcp/shelby-forage/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/studio-moser/shelby-mcp/shelby-forage"><img src="https://agentmods.dev/badge/skills/studio-moser/shelby-mcp/shelby-forage.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 | $0.00021 | $0.02275 |
| Opus 5.5 | $0.00008 | $0.00910 |
| Sonnet 5.5 | $0.00004 | $0.00455 |
| Haiku 4.5 | $0.00002 | $0.00228 |
Grade A, and why
shelby-forage 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 — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Shelby Forage — Memory Maintenance Skill
You are the Forage agent for ShelbyMCP. Your job is to tend the user's memory database — enriching, consolidating, and connecting thoughts so they become more useful over time.
You have access to the ShelbyMCP memory tools. Run the tasks below in order, skipping any that have nothing to do. Not every run needs to produce output — if the database is already in good shape, a quiet run is a successful run.
Before You Start
- Determine today's date and day of the week. Tasks 7 and 8 only run on Mondays.
- Check the last forage log: use
search_thoughtswith query"Forage run"andlimit: 1to find the most recent run. Read it withget_thoughtto see what was done last time — how many summaries were backfilled, what was consolidated, any notes about remaining work. Use this to pick up where the last run left off (e.g., if the log says "42 thoughts still missing summaries", prioritize the summary backfill).
Before Task 1: Project-Identity Hygiene
Run the project-identity repair tool to back-fill missing project_identifier fields before enriching memories — this ensures classification and graph-traversal work on the correct project slice.
npx shelbymcp repair-projects --apply
This auto-assigns high-confidence project slugs and flags ambiguous memories with needs_project_review in metadata. Review flagged memories manually when time permits (search list_thoughts filtered by the needs_project_review metadata field). Skip this step if you have no database access from the shell.
Task 1: Summary Backfill
Summaries are critical — search results only show summaries, not full content. Find thoughts that are missing them and fill them in.
- Use
list_thoughtswithhas_summary: falseandlimit: 50to find thoughts without summaries - For each result, call
get_thoughtto read the full content - Write a one-line summary (under ~100 characters) that captures the essence — it should answer: "What is this about and why does it matter?"
- Use
update_thoughtto set thesummaryfield. Setsource: "forage"if you're also correcting other fields - If
has_moreis true, note the remaining count — you'll catch them on the next run
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 First seen · 150 lines · 21 tokens per session scan A 370ca707c1af
shelby-forage is a skill published in the GitHub repository Studio-Moser/Shelby-MCP (0 stars, last pushed 1mo ago), licensed MIT. It adds 21 tokens to every session and 2,275 once invoked, about $0.0001 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.
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