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 instructions/manojbajaj95/agent-knowledge-cards/agents-mdgit clone --depth 1 https://github.com/manojbajaj95/agent-knowledge-cardsWrote 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/manojbajaj95/agent-knowledge-cards/agents-md)<a href="https://agentmods.dev/instructions/manojbajaj95/agent-knowledge-cards/agents-md"><img src="https://agentmods.dev/badge/instructions/manojbajaj95/agent-knowledge-cards/agents-md.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 | $0.00879 | $0.00879 |
| Opus 5 | $0.00439 | $0.00439 |
| Sonnet 5 | $0.00176 | $0.00176 |
| Haiku 4.5 | $0.00088 | $0.00088 |
Grade A, and why
agent-knowledge-cards 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 today.
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 — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Always talk in ASD-STE100 Simplified Technical English. Also follow Zinsser's four principles of quality writing:
- Simplicity
- Brevity
- Clarity
- Humanity
Conventions for agents working in this repo.
Layout
Two boxes: memory (save, store, retrieve) and harness (fetch + reflect). Adapters wrap host envelopes only.
src/memory/— L1 card internals (ingest, retrieve, storage, markdown) + persist ops (ops.ts). Host-agnostic.src/harness/— session fetch (fetchCards) + reflect follow-up (reflectFollowup, REFLECT.md). Not a host SDK.src/cli/— thin CLI over memory (status,query,propose,update,delete,mcp) plusinstall(adapter wiring).initis hidden; propose creates dirs.src/adapters/— host hook envelopes (Claude Code / Cursor / Codex) and the Pi extension. Do not importsrc/memory.src/mcp/— MCP stdio server (@modelcontextprotocol/sdk); tool logic intools.ts.eval/— Harbor A/B with/without knowcards (eval:prepare/eval:run/eval:compare). Primary validation for this slice (manual; not CI). Sequential same-repo runs are named only.tests/— offline checks for retrieve/fetch and the eval pipeline. No separate unit-test suite beyond that.dist/— build output for npm /npx(do not edit; emit withbun run build).
On-disk cards
Filesystem-first: cards are local markdown only (.agents/knowledge_cards/<notebook-id>/*.md). No DB backend yet. propose creates notebook dirs as needed (init is hidden; not a required step). Process start loads the full library into memory via openLibrary.
Commands
bun install
pre-commit install # once per clone
bun test # eval pipeline offline checks only
bun run typecheck
bun run lint
bun run build
bun run knowcards install cursor|claude-code|codex|pi
bun run knowcards status|query|propose|update|delete|mcp
bun run eval:prepare # Harbor — manual
bun run eval:run -- --task pytest-dev__pytest-10051 --agent oracle
bun run eval:run -- --task pytest-dev__pytest-10051 # [email protected] + openai/gpt-5.6-luna
bun run eval:run # four SWE-bench Verified tasks
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.
- today Changed · +18 tokens per session 7f5f592ada20
- 5d ago First seen · 59 lines · 861 tokens per session scan A 05239ef128e7
agent-knowledge-cards AGENTS.md is an instructions file published in the GitHub repository manojbajaj95/agent-knowledge-cards (4 stars, last pushed 5d ago), licensed MIT. It adds 879 tokens to every session, about $0.0044 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 2026-08-31.
Other instructions, from other repositories
hindsight CLAUDE.md
Claude Code instructions for vectorize-io/hindsight, covering claude.md, project overview, development commands, local development (api + ui) and start both api server and control plane ui.
hindsight AGENTS.md
AGENTS.md instructions for vectorize-io/hindsight: See CLAUDE.md for project documentation and coding conventions.
InvOS AGENTS.md
AGENTS.md instructions for felipenalves/InvOS, covering agents.md — invos (sistema operacional do negócio), contexto do negócio, primeira vez, fluxo de trabalho and aprender com correções.
memory-lancedb-mcp CLAUDE.md
Claude Code instructions for cablate/memory-lancedb-mcp, covering claude.md, project principles, git workflow, development commands and architecture.
opengeni CLAUDE.md
Claude Code instructions for Cloudgeni-ai/opengeni, a project described as: Open, self-hostable agentic runtime for organizations — durable, replayable agent sessions, human approvals, governed credentials and memory, running in managed sandboxes or on your own hardware. Apache-2.0.
InvOS CLAUDE.md
Claude Code instructions for felipenalves/InvOS, a project described as: INVOS — memória pro seu agente de IA. Para de reexplicar quem você é em toda sessão. Multi-harness (Cursor, Claude, Codex, Grok…).