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/xobotyi/cc-foundry/researchnpx skills add xobotyi/cc-foundry --skill researchgit clone --depth 1 https://github.com/xobotyi/cc-foundryWrote 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/xobotyi/cc-foundry/research)<a href="https://agentmods.dev/skills/xobotyi/cc-foundry/research"><img src="https://agentmods.dev/badge/skills/xobotyi/cc-foundry/research.svg" alt="Measured on agentmods" 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 | $0.00043 | $0.02779 |
| Opus 5 | $0.00022 | $0.01389 |
| Sonnet 5 | $0.00009 | $0.00556 |
| Haiku 4.5 | $0.00004 | $0.00278 |
Grade A, and why
research 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 yesterday.
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 — 272 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research
Objective codebase investigation that produces factual findings blind to the intent expressed in the discovery brief. The lead reads the brief and generates neutral questions. Teammates investigate the codebase. The lead compiles findings. No teammate ever sees the brief, the ticket, or the user's goals.
Environment
Agent teams: !echo ${CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS:-disabled}
Prerequisites
-
If agent teams shows
disabledabove, stop immediately and tell the user:Agent teams are required for parallel research. Enable them by adding to your settings:
{ "env": { "CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS": "1" } }Then restart the session.
Teammates also need an interactive session. Under
claude -p, a named spawn runs as an ordinary subagent — the waves still work, but findings return as subagent results instead ofSendMessage. -
Locate the brief:
- Discovery handoff — the brief is already in conversation context. Use it directly.
- Standalone invocation —
$ARGUMENTSnames a brief, or ask the user to provide one. Read it into conversation context — the skill works from context. - If no brief exists in conversation or on disk, ask the user whether to run discovery first.
Process
Phase 1 — Plan and Dispatch
- Read the brief from conversation context.
- Identify the codebase scope clusters the brief touches (modules, directories, subsystems).
- For each scope, formulate the questions worth investigating. Follow the question generation rules below.
- Multiple questions per scope is normal. Group questions that share files to avoid duplicate reads across teammates.
- Don't fix a question count up-front. Let the brief's complexity determine how many.
- The brief's Questions for research list (facts discovery deferred) is mandatory input — every entry becomes an investigation question, rewritten through the same neutrality rules as any other.
- Self-check questions against the bias validation gate.
- For each scope cluster, create a task via TaskCreate using the task description format below, then spawn one teammate
via Agent with
subagent_type: "codebase-researcher",name: "researcher-{scope-slug}", and an intent-free spawn prompt (see Spawn Prompt below).- The
nameis what makes the spawn a teammate, and it is the address other agents use to message it. There is no team to create — the session owns one team — andteam_nameis ignored. - Task descriptions contain only questions and scope boundaries. Never the brief, ticket, or intent.
- Explicit
subagent_typeensures the teammate inherits the agent's tool restrictions and system prompt; without it, the platform falls back to the general-purpose agent. - If this session has no Task tools, skip TaskCreate and put the task description block in the spawn prompt instead. It carries only questions and scope, so the information barrier holds.
- The
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.
- yesterday First seen · 272 lines · 43 tokens per session scan A 5cfb6eb476ce
research is a skill published in the GitHub repository xobotyi/cc-foundry (20 stars, last pushed 2d ago), licensed MIT. It adds 43 tokens to every session and 2,779 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 2026-09-04.
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