Borrowing it
Nothing to install: this file belongs to joshua-auchincloss/factsets. 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/joshua-auchincloss/factsets/main/AGENTS.mdgit clone --depth 1 https://github.com/joshua-auchincloss/factsetsWrote 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/instructions/joshua-auchincloss/factsets/agents-md)<a href="https://agentmods.dev/instructions/joshua-auchincloss/factsets/agents-md"><img src="https://agentmods.dev/badge/instructions/joshua-auchincloss/factsets/agents-md/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/instructions/joshua-auchincloss/factsets/agents-md"><img src="https://agentmods.dev/badge/instructions/joshua-auchincloss/factsets/agents-md.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 | $0.00755 | $0.00755 |
| Opus 5.5 | $0.00302 | $0.00302 |
| Sonnet 5.5 | $0.00151 | $0.00151 |
| Haiku 4.5 | $0.00076 | $0.00076 |
Grade A, and why
factsets AGENTS.md 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 2mo 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 — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Instructions
This project uses Factsets for persistent knowledge management.
Required Behavior
- Use Factsets tools on EVERY prompt without exception
- Never wait for user to ask - be proactive
- Validate context before responding:
search_facts,search_skills - Capture all learnings immediately:
submit_facts - Register all fetched URLs:
add_resources - Log all successful commands:
submit_execution_logs - Check preferences before generating output:
get_preference_prompt
Pre-Response Checklist
Before responding to any user prompt:
- Did I
search_factsfor relevant domain knowledge? - Did I
search_skillsif this involves a procedure? - Am I about to claim something I should verify first?
- Will my response involve code? Check
get_preference_prompt - Am I learning something new? Prepare to
submit_facts
Prompt Classification
| Prompt Type | Primary Tools | Search Strategy |
|---|---|---|
| Question about project | search_facts |
Tags from question + "project" |
| Debug/fix request | search_facts + search_execution_logs |
Error keywords, component tags |
| "How do I..." | search_skills |
Task-related tags |
| Code generation | search_facts + get_preference_prompt |
Domain tags + code style |
| Research request | search_resources |
Domain tags |
Tag Strategy
- Extract nouns from prompt: "Fix the database migration" -> database, migration
- Add context: What component? What domain? -> drizzle, schema
- Include action type: fix -> bugs, debugging, issues
- Use hierarchy: If unsure, use broader parent tag
During Long Tasks
For multi-step work, use Factsets between steps - do not wait until completion:
- After each successful command:
submit_execution_logs - After discovering something:
submit_facts - After fetching external content:
add_resources
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.
- 2mo ago First seen · 87 lines · 755 tokens per session scan A 882a1aead56f
factsets AGENTS.md is an instructions file published in the GitHub repository joshua-auchincloss/factsets (1 stars, last pushed 7mo ago), licensed MIT. It adds 755 tokens to every session, about $0.0030 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.
factsets AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| factsets AGENTS.mdjoshua-auchincloss/factsets | Instructions file | 1 | 7mo ago | MIT | A | 755 | Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | yesterday | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | yesterday | MIT | A | 4,680 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 5,516 | GitHub Copilot |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |