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/kamiazya/whiteboard/agents-mdgit clone --depth 1 https://github.com/kamiazya/whiteboardWrote 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/kamiazya/whiteboard/agents-md)<a href="https://agentmods.dev/instructions/kamiazya/whiteboard/agents-md"><img src="https://agentmods.dev/badge/instructions/kamiazya/whiteboard/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 | $0.04038 | $0.04038 |
| Opus 5 | $0.02019 | $0.02019 |
| Sonnet 5 | $0.00808 | $0.00808 |
| Haiku 4.5 | $0.00404 | $0.00404 |
Grade A, and why
whiteboard 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 — 285 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Project Instructions
Use this repo's standard development loop for every feature, bug fix, or refactor:
- Start with the smallest failing test at the nearest layer.
- Make the smallest patch that turns it green.
- Manually verify the real behavior in a running app or browser.
- Lock the verified user flow into
canvas-viewer-browser/web-browseror a broader E2E test when browser-mode is not enough.
Test Layer Selection
Start with the smallest failing test at the nearest layer, and do not jump to broad E2E when a smaller failing test can isolate the bug. Reach for a property or model-based test (fast-check) over an example-only one when the change touches a parser/serializer, a state machine with time/TTL/revocation semantics, a concurrent store, a CRDT or other mergeable structure, or a rounding/normalization transform with an algebraic invariant. Prefer example and browser tests for UI wiring, one-off integrations, and anything with no clean invariant to state.
Everything that follows from that choice is the test-layer-selection skill: which project
serves which layer and the command for each, the per-layer numRuns budget, and the property
disciplines — mutation-check every new property, answer a vacuous one with a denser generator
rather than more runs, never pin a seed, and never build an oracle out of the code it is judging.
Coverage ledgers are .claude/rules/coverage-ledger.md, which is path-scoped and loads itself.
Required Workflow
1. Write the red test first
- Reproduce the bug or target behavior before changing production code.
- Keep the first failing case as small and local as possible.
2. Turn it green locally
Run the narrowest project first:
pnpm test --project mcp-node
pnpm test --project canvas-viewer-jsdom
pnpm test --project canvas-viewer-browser
After the targeted test passes, run the broader suite that covers the touched area.
3. Manually verify the real behavior
- For UI work, open the real screen and confirm the behavior directly.
- Prefer Chrome DevTools MCP or Playwright MCP when available to inspect DOM, console, network, and visible behavior.
- If the changed flow is represented by a project skill under
./skills/*, read the relevantSKILL.mdand dogfood the real MCP/skill flow instead of verifying only through mocks. - While dogfooding, collect friction, awkward prompts, missing affordances, and ideas for follow-up improvements.
- Record every still-open dogfooding finding as a whiteboard document issue (see the
ticketingskill). When it is fixed, change it totype: notewith aRESOLVED —name and say what fixed it — do not delete it. What the document accumulated is the measurements, and those are what stop it being investigated again. - If runtime behavior disagrees with the test, treat runtime as the source of truth and fix the test or implementation.
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 · +1 lines · +29 tokens per session 312781727a29
- yesterday Changed · -166 lines · -2,371 tokens per session 3cb00c63c9a3
- 5d ago First seen · 450 lines · 6,380 tokens per session scan A 757434374135
whiteboard AGENTS.md is an instructions file published in the GitHub repository kamiazya/whiteboard (6 stars, last pushed today), licensed Apache-2.0. It adds 4,038 tokens to every session, about $0.0202 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
digital-service-orchestra skills.instructions.md
Instructions for navapbc/digital-service-orchestra, a project described as: Workflow infrastructure plugin for Claude Code projects — TDD-driven sprint management, review gates, hook parameterization, and multi-stack config.
spec-driven-tdd AGENTS.md
Instructions for strelov1/spec-driven-tdd: This repo is a skill-pack. When implementing an OpenSpec change, invoke the spec-driven-tdd skill and follow its lifecycle: plan in OpenSpec, isolate in a worktree, implement each task via TDD → simplify → review, then finish + archive.
mcp-repo-onboarding AGENTS.md
Instructions for rogermt/mcp-repo-onboarding, covering agents.md — agent & copilot instructions, current status, output verification, project identity and ⚠️ critical: tdd required.
speckit AGENTS.md
AGENTS.md instructions for jmanhype/speckit, covering agents.md - instructions for ai coding agents, core philosophy, pivotal methodology alignment, pivotal-style epic format and priority levels (pivotal-aligned).
arxiv-agent-mcp AGENTS.md
AGENTS.md instructions for tbaraniuk/arxiv-agent-mcp, covering agents.md, roles, test-writer, implementer and per-task loop.
opencode-copilot-instructions AGENTS.md
AGENTS.md instructions for ekroon/opencode-copilot-instructions, covering agent instructions, orchestration pattern, 1. always orchestrate (unless being orchestrated), 2. test-driven development (tdd) and tdd workflow for each module.