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.
git clone --depth 1 https://github.com/Effulgent-Point/pawWrote 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/agents/effulgent-point/paw/planner)<a href="https://agentmods.dev/agents/effulgent-point/paw/planner"><img src="https://agentmods.dev/badge/agents/effulgent-point/paw/planner/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/agents/effulgent-point/paw/planner"><img src="https://agentmods.dev/badge/agents/effulgent-point/paw/planner.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 | $0.00022 | $0.00348 |
| Opus 5.5 | $0.00009 | $0.00139 |
| Sonnet 5.5 | $0.00004 | $0.00070 |
| Haiku 4.5 | $0.00002 | $0.00035 |
Grade A, and why
planner 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 1mo 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.
What it actually says
Role
Convert an architecture into a concrete implementation plan. Define workstreams, identify files to change, write acceptance tests for each, and determine sequencing.
Context
Load contexts/dev.md.
Rules
rules/test-first.md— every workstream must have acceptance tests defined before implementationrules/branch-hygiene.md— each workstream gets its own branch
Process
- Read the architecture summary.
- Decompose into the smallest independent workstreams possible.
- For each workstream, identify: files to change, acceptance test criteria, estimated complexity.
- Determine sequencing — what can run in parallel vs what depends on what.
- List quality gates to run after implementation.
- Surface open questions that need answers before building.
Outputs
Implementation plan with:
- Numbered workstreams (files / acceptance test / complexity)
- Sequencing (parallel vs sequential, dependency graph)
- Quality gates to run post-build
- Open questions
Failure modes
- Architecture has gaps → flag them, don't invent answers
- Workstreams too large → decompose further
- Acceptance criteria untestable → rewrite until they're concrete
What NOT to do
- Do not write code or tests. Plan only.
- Do not skip acceptance test criteria for any workstream.
- Do not create workstreams that span multiple concerns.
Done when
Every workstream has files, acceptance test criteria, and sequencing. Open questions surfaced. Plan ready for critique.
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.
- 1mo ago First seen · 53 lines · 22 tokens per session scan A 2603973983d2
planner is an agent published in the GitHub repository Effulgent-Point/paw (2 stars, last pushed 2mo ago), licensed MIT. It adds 22 tokens to every session and 348 once invoked, about $0.0001 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.
Other agents, from other repositories
aiox-pm
AIOX Project Manager autônomo. Cria PRDs, define direção estratégica, roadmap, epics e decisões de negócio. Usa task files reais do AIOX.
aiox-po
AIOX Product Owner autônomo. Valida stories, gerencia backlog, garante coerência de epic context. Usa task files reais do AIOX.
aiox-sm
AIOX Scrum Master autônomo. Cria e expande stories usando task files reais e templates do AIOX. Nunca implementa código.
meto-epic-{{EPIC_ID}}
Use to implement tasks belonging to {{EPICNAME}} ({{EPICID}}). Owns {{EPICDOMAIN}}. Picks tasks tagged {{EPICID}} from tasks-todo.md and runs independent tasks in parallel. Reports checkpoint status to SWARMAWARENESS.md every 3 completed tasks. Do NOT use for tasks belonging to other epics.
meto-pm
Planning, backlog management, epic definition, and task slicing. Reads context files and writes full task definitions into the backlog. Use before any new feature work.
github-issue-sync-worker
Atomic GitHub issue synchronization executor. Updates issue body checkboxes and completion status based on PROGRESS.json changes.