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/fmilioni/agents-board/plannpx skills add fmilioni/agents-board --skill plangit clone --depth 1 https://github.com/fmilioni/agents-boardWrote 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/fmilioni/agents-board/plan)<a href="https://agentmods.dev/skills/fmilioni/agents-board/plan"><img src="https://agentmods.dev/badge/skills/fmilioni/agents-board/plan.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 5.1 | $0.00113 | $0.03426 |
| Opus 5 | $0.00056 | $0.01713 |
| Sonnet 5 | $0.00023 | $0.00685 |
| Haiku 4.5 | $0.00011 | $0.00343 |
Grade A, and why
plan 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 5d 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 — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Planning a demand into cards
Turn a demand into work that a fresh agent with zero context can pick up and build. The artifact is the cards in Agents Board — not a spec file, not a message in the chat.
Load the
agents-boardskill first if it isn't loaded in this conversation — it covers the project binding, the board's tools and conventions this skill builds on.
Hard rule: do not write code, scaffold, edit files or mutate the board until the user has approved the plan. This holds for every demand — "too simple to plan" is exactly where a wrong assumption gets baked in. The plan can be three sentences, but you present it and get approval.
Flow
Run in order. Steps 3–6 are the whole point of the skill; none of them is optional, though a small demand passes through them fast.
- Understand the demand. Read what the user wrote and restate the goal in one sentence. If they described several independent systems (a chat platform and storage and billing and analytics), stop: propose a sequence and plan one module at a time.
- Explore what already exists. Resolve the project (binding first). Then read:
search_docsfor the decisions and module knowledge that touch this area,search_cardsplus the opentodo/backlogcards for work that overlaps, and the actual code paths involved. Never propose against a blank slate.- Extend, don't stack. If the demand only extends a card that hasn't started (
todo/backlog), update that card after approval instead of creating a twin. Once a card isin_progressit's locked — the demand becomes its own card. Unsure it's the same deliverable? Ask.
- Extend, don't stack. If the demand only extends a card that hasn't started (
- First clarification round — remove the doubts you already have. Make it unambiguous what is being built: goal, scope, constraints, acceptance. Two things to resolve, both with the user (see Never decide alone): ambiguities (what they actually want) and missing pieces (a brief is almost always incomplete — it asks for login but never says which hash, asks for a list but never says empty/error states). Hunt the gaps; don't fill them silently.
- Offer research — never run it unannounced. See Research is an offer. Ask whether to dig deeper, say what each option would answer and whether you think it's worth it, and run only what the user picks.
- Second clarification round — only what the research opened. Research routinely surfaces a fork that didn't exist before ("this library needs a background worker — where does it run?"). Take those back to the user the same way, with a recommended default. Don't re-ask what round 1 already settled.
- Present the design for approval. Lay out what will be built, section by section: a direct demand in a few sentences, a complex one in ~200–300 words. Where there's a real fork, give 2–3 approaches with trade-offs, your recommendation and why. Include the proposed card breakdown in one line each. Revise until the user approves — only then create anything.
- Create the cards — see Writing a card, Sizing a card and Where the work lives.
- Self-review the cards with fresh eyes and fix inline — see Self-review.
- Hand off. Present the final set (each key + one line, grouped by story). Execution is the user's workflow, whatever it is; the board contract for it lives in the
agents-boardskill — move the card toin_progress, land it inreviewwith a test-plan comment, anddoneonly on the user's approval. - Close the inbox loop. For every inbox demand you planned,
mark_inbox_planned(id, cardKeys[])(a discarded one isn't marked — ask the user toarchive_inboxordestroy_inbox). Then re-checklist_inboxfresh — the user may have dropped something while you planned; offer once to plan what isn't covered.
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.
- 5d ago First seen · 126 lines · 113 tokens per session scan A 4bdfea26c917
plan is a skill published in the GitHub repository fmilioni/agents-board (0 stars, last pushed 5d ago), licensed MIT. It adds 113 tokens to every session and 3,426 once invoked, about $0.0006 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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