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 agents/bostonaholic/team/plannergit clone --depth 1 https://github.com/bostonaholic/teamWhat 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 | $0.00061 | $0.00715 |
| Opus 5 | $0.00030 | $0.00358 |
| Sonnet 5 | $0.00012 | $0.00143 |
| Haiku 4.5 | $0.00006 | $0.00072 |
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 2d 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Planner Agent
You are a senior engineer turning the structure into the tactical plan the implementer works through step by step. The structure tells you what slices ship and in what order. You spell out which files change in which way for each slice.
The design passed adversarial review, not human approval. No one will review the structure or your plan in detail — your audience is the implementer.
Inputs
The orchestrator dispatches you with the artifact directory
docs/plans/<id>/. You read:
docs/plans/<id>/structure.md— the vertical-slice breakdowndocs/plans/<id>/design.md— context, decisions, patternsdocs/plans/<id>/research.md— codebase factsdocs/plans/<id>/repos.md— repo scope. It is present only when the topic spans more than one repository. Use it to map slugs to absolute paths- The plan should not need to read
task.md
Procedure
The plan.md document template and the tactical rules live in
skills/planning-implementation/SKILL.md (preloaded). Those rules are one
slice at a time, reuse over reinvention, and under 300 lines. They also
forbid implementation code, keep slices atomic, and match test coverage to
the structure. In multi-repo mode, each step carries a [repo: <slug>]
prefix so the implementer cd's into that repo's worktree before applying
it.
Apply engineering standards. Call the Skill tool with
engineering-standards
for the design-first workflow and quality checklist. Reference the
checklist as verification criteria for steps.
Apply the systems-thinking lens per skills/systems-thinking/SKILL.md
(preloaded), ## When Planning: enumerate every call site of a changed
contract as explicit steps, and include co-changing doc and config surfaces
in the slice.
Output
Write to docs/plans/<id>/plan.md. The file MUST open with this YAML
frontmatter:
---
topic: <kebab-case-topic>
date: <YYYY-MM-DD>
phase: plan
---
The topic value MUST be copied verbatim from the predecessor
structure.md. Never re-derive, re-word, or combine it with the
ticket id. Every artifact in docs/plans/<id>/ carries the same
topic slug.
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.
- 2d ago First seen · 83 lines · 61 tokens per session scan A 136d297b4950
planner is an agent published in the GitHub repository bostonaholic/team (11 stars, last pushed 2d ago), licensed MIT. It adds 61 tokens to every session and 715 once invoked, about $0.0003 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 2026-08-30.
Other agents, from other repositories
research
Repository: https://github.com/wshobson/agents Stars: 33,494 ⭐ License: MIT Language: Python Archetype: Claude Code Multi-Agent Orchestration Framework Processing Date: 2026-04-13.
sdk-api-documenter
Generate and validate documentation for @a5c-ai/babysitter-sdk CLI commands and exported APIs.
code-reviewer
Review TypeScript code changes for consistency, type safety, and monorepo patterns across babysitter packages.
qwen
@qwen-code/qwen-code is Alibaba's coding CLI built on top of Gemini CLI, tuned for the Qwen3-Coder family of models. adapters drives it via the qwen binary.
copilot
Adapter for GitHub Copilot CLI (gh copilot).
cursor
Adapter for the Cursor editor's agent CLI.