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/mvpr-ext-projects/planday-bridge/claude-mdgit clone --depth 1 https://github.com/MVPR-Ext-Projects/planday-bridgeWrote 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/mvpr-ext-projects/planday-bridge/claude-md)<a href="https://agentmods.dev/instructions/mvpr-ext-projects/planday-bridge/claude-md"><img src="https://agentmods.dev/badge/instructions/mvpr-ext-projects/planday-bridge/claude-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 | $0.01398 | $0.01398 |
| Opus 5 | $0.00699 | $0.00699 |
| Sonnet 5 | $0.00280 | $0.00280 |
| Haiku 4.5 | $0.00140 | $0.00140 |
Grade A, and why
planday-bridge CLAUDE.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 3d 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 — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
planday-bridge
AGENTS.md is the canonical context file — architecture, the traps, and the rules that must not be weakened. Read it before changing anything.
Setting this up for someone (agent playbook)
If a user has just arrived here and asked you to get it working, this is the sequence. Most of it you can do; two steps you cannot, and should hand back.
Prerequisites: Node 20 or newer. pnpm is what the lockfile is for, but npm install
works fine — check which is available rather than assuming.
Step 1 — prove it runs locally, before any credentials.
pnpm install && pnpm dummy # or: npm install && npm run dummy
Expect a table and ~626 rows of sample data. If that works, the whole pipeline works and anything that fails later is configuration, not code.
Step 2 — the user must fetch their own Planday credentials. You cannot.
It needs an admin login to their Planday portal in a browser. Ask them to go to Settings → Integrations → API Access → Create App, tick the scopes listed in SETUP.md, click Authorise, and copy the Client ID and Refresh Token.
Do not ask them to paste those values into the chat. A Planday refresh token grants access to staff and payroll data and does not expire on its own. Instead, create the file for them and have them fill it in:
cp .env.example .env && open -e .env # or: code .env
Then run pnpm doctor. It checks environment, configuration, connection, every Planday
scope separately, and a real report build, reporting each layer in order - fix the first
FAIL, since later checks depend on earlier ones. Its output contains no credentials or
staff data, so it is safe to quote back to the user or paste into an issue. Read the
output, never the token.
Step 3 — deploy. You can drive this, but the secrets step is theirs.
The README has a one-click Vercel button, which is the better route for a non-technical user. From a terminal:
npm i -g vercel
vercel login
vercel link # creates the project
# Ask the user to run these three themselves and type the values at the prompt,
# so the secrets never enter this transcript or their shell history.
vercel env add PLANDAY_CLIENT_ID production
vercel env add PLANDAY_REFRESH_TOKEN production
vercel env add BRIDGE_KEY production # any long random password they choose
vercel deploy --prod
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.
- 3d ago First seen · 132 lines · 1,398 tokens per session scan A 3fc68641cc24
planday-bridge CLAUDE.md is an instructions file published in the GitHub repository MVPR-Ext-Projects/planday-bridge (0 stars, last pushed 9d ago), licensed MIT. It adds 1,398 tokens to every session, about $0.0070 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.
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