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 skills add rjmurillo/ai-agents --skill plannergit clone --depth 1 https://github.com/rjmurillo/ai-agentsWrote 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/rjmurillo/ai-agents/planner)<a href="https://agentmods.dev/skills/rjmurillo/ai-agents/planner"><img src="https://agentmods.dev/badge/skills/rjmurillo/ai-agents/planner.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 | $0.00060 | $0.02356 |
| Opus 5 | $0.00030 | $0.01178 |
| Sonnet 5 | $0.00012 | $0.00471 |
| Haiku 4.5 | $0.00006 | $0.00236 |
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 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 — 335 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Planner Skill
Purpose
Two workflows for complex tasks:
- Planning workflow (planner.py): Create and review implementation plans
- Execution workflow (executor.py): Execute approved plans through delegation
Invocation Routing
Invoke planner.py when user asks to:
- "plan", "design", "architect" a feature
- "review" an existing plan
- Break down a complex task into milestones
Invoke executor.py when user asks to:
- "execute", "implement", "run" a plan
- "resume" or "continue" execution
- Provides a plan file path for implementation
When to Use
Use the planner skill when the task has:
- Multiple milestones with dependencies
- Architectural decisions requiring documentation
- Migration steps that need coordination
- Complexity that benefits from forced reflection pauses
When to Skip
Skip the planner skill when the task is:
- Single-step with obvious implementation
- A quick fix or minor change
- Already well-specified by the user
Scripts
| Script | Purpose |
|---|---|
scripts/planner.py |
Planning and review workflow with step-based state management |
scripts/executor.py |
Execution workflow for approved plans with milestone delegation |
Triggers
| Trigger Phrase | Operation |
|---|---|
plan this feature |
planner.py (planning phase) |
create implementation plan |
planner.py (planning phase) |
review the plan and pick up next item |
executor.py (execution phase) |
execute the plan at plans/X.md |
executor.py (execution phase) |
resume execution |
executor.py (continue from last step) |
Anti-Patterns
| Avoid | Why | Instead |
|---|---|---|
| Skipping review phase after planning | Misses quality/temporal issues | Always run review steps 1-2 before execution |
| Starting execution without /clear | Context pollution from planning | User should /clear before execution workflow |
| Manually following workflow steps | Script manages state and transitions | Run the script and follow its output |
| Planning single-step tasks | Overhead exceeds benefit | Implement directly without planner |
| Editing plan during execution | Creates drift between plan and actions | Return to planning phase for changes |
What ships with it
13 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/agent-architecture-patterns.md 2.2 KB
- references/design-pit-of-success.md 3.2 KB
- references/DEVELOPMENT.md 3.9 KB
- references/explainers-and-intents.md 2.7 KB
- references/hybrid-memory-architecture.md 2.2 KB
- references/mental-models-galls-law.md 2.3 KB
- references/strategy-ooda-loop.md 2.4 KB
- resources/default-conventions.md 3.8 KB
- resources/diff-format.md 7.9 KB
- resources/plan-format.md 6.1 KB
- resources/temporal-contamination.md 6.0 KB
- scripts/executor.py 26 KB runs code
- scripts/planner.py 26 KB runs code
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 · 335 lines · 60 tokens per session scan A 37e67b69f382
planner is a skill published in the GitHub repository rjmurillo/ai-agents (45 stars, last pushed today), licensed MIT. It adds 60 tokens to every session and 2,356 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 2026-09-03.
Other skills, from other repositories
linear-cli
Use when the user wants to list, view, start, create, or update Linear issues from the terminal via schpet/linear-cli, including setup, auth, repo config, and safe read/write boundaries.
ci-cd
A guide for designing automated build and delivery workflows with GitHub Actions. These workflows can run checks such as tests, code-quality scans, coverage checks, and builds when code is pushed or a pull request is opened.
crew-lifecycle
Use this skill when coordinating a live crew across hierarchy, approvals, and boards.
team-plan-review
Use this skill when leading a crew that must submit an execution plan before work starts.
proactive-memory
Turn repeated failures, corrections, and recurring requests into durable follow-up work.
matrix-ops
Use Matrix when work crosses rooms, bridges, or federated teams that need durable plain-text coordination.