agents

agents is a skill for Claude Code, Codex from IlkhamFY/epistemic-foraging. It costs 0 tokens per session (720 once invoked), scanned A, original, Apache-2.0.

Instructions that guide an AI agent through structured research using the foragekit MCP server, a tool connection for searching and reading sources. The process starts by recording the research question, then finds and reads relevant evidence.

In plain words
What is it for?
Use it to research a topic, follow citations from important sources, fetch available full text, and read it in focused sections.
Why use it?
It helps avoid endless keyword searches and unfocused reading. The agent can track open questions and choose sources based on likely information value.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to research a topic, follow citations from important sources, fetch available full text, and read it in focused sections.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ilkhamfy/epistemic-foraging/agents
Install

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.

Any agent
npx skills add IlkhamFY/epistemic-foraging --skill agents
Clone the repo
git clone --depth 1 https://github.com/IlkhamFY/epistemic-foraging

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for agents

README.md
[![agentmods](https://agentmods.dev/badge/skills/ilkhamfy/epistemic-foraging/agents.svg)](https://agentmods.dev/skills/ilkhamfy/epistemic-foraging/agents)
Your own site
<a href="https://agentmods.dev/skills/ilkhamfy/epistemic-foraging/agents"><img src="https://agentmods.dev/badge/skills/ilkhamfy/epistemic-foraging/agents.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 720 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00000 $0.00720
Opus 5 $0.00000 $0.00360
Sonnet 5 $0.00000 $0.00144
Haiku 4.5 $0.00000 $0.00072

Measured 8d ago against content hash 204906d96ff3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

agents 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 8d 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.

agents/SKILL.md · 54 lines

How it starts

The opening of the file, as written. The whole thing — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: epistemic foraging with foragekit

Drop-in instructions for any AI agent connected to the foragekit MCP server (uvx foragekit serve --mcp). Paste this into your agent's instructions, or install it as a skill. It teaches the loop; the tools enforce the rules.

The loop

  1. Register the question first. Call forage_ask with the user's research question before searching anything. Every later step is prioritized against open questions. Resuming an old workspace? Start with forage_list_questions to recover ids and state.
  2. Search wide, then snowball. Use forage_search for 1–2 broad queries, then forage_snowball from the most central results instead of endlessly rephrasing keywords — citation walks find what keyword search can't.
  3. Read by expected information gain, not list order. Call forage_frontier and read what it ranks highest — it balances relevance, novelty, and centrality against reading cost. When the response says patch_exhausted, believe it: switch queries or clusters instead of grinding a dead patch.
  4. Fetch, then read in windows. forage_fetch_text caches full text when licensing allows (it reports why when it can't). Read with forage_get_source_text windows — never try to hold a whole paper in context. Mark what you've processed with forage_mark_read.
  5. Pin before you claim. Never state a finding without evidence. Use forage_find_text with approximate wording to get the exact span and locator, then forage_pin_evidence. Pins are verification-tiered (full-text / abstract / unverified) — prefer the strongest tier available.
  6. Claim with honest stance and confidence. forage_add_claim links evidence with explicit stances — record contradicts links when sources disagree; contested claims are a finding, not a failure. State confidence as your actual credence, not politeness (it is author-stated and audited later, not decoration).
  7. Audit before you present. Run forage_audit and fix what it flags — unsupported claims, single-source claims, stale pins — before compiling.
  8. Compile the brief to a file. forage_brief with out_path writes the self-contained artifact and returns only a summary, keeping your context clean. Then forage_update_question to resolve or re-grade the question.

Read the full file on GitHub · 54 lines

Changes

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.

  1. 8d ago First seen · 54 lines · 0 tokens per session scan A 204906d96ff3

Subscribe to this mod's changes

agents is a skill published in the GitHub repository IlkhamFY/epistemic-foraging (2 stars, last pushed 1mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 720 tokens. 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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