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/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/skills/rjmurillo/ai-agents/planner"><img src="https://agentmods.dev/badge/skills/rjmurillo/ai-agents/planner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Memory Poisoning · line 232 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
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 | $0.00147 | $0.02665 |
| Opus 5.5 | $0.00059 | $0.01066 |
| Sonnet 5.5 | $0.00029 | $0.00533 |
| Haiku 4.5 | $0.00015 | $0.00266 |
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 24d 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 — 352 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Planner Skill
Purpose
Two script-guided workflows. Each script prints the guidance for one numbered step; the caller passes the step number and its thoughts on every call, and nothing is saved between calls:
- Planning workflow (planner.py): Draft a plan through forced reflection pauses, then run the technical-writer and quality-reviewer review of the plan file
- Execution workflow (executor.py): Execute an approved plan file through delegation. On resume, step 1 reconciles the plan file against work already done
The plan skill owns lifecycle decomposition of a spec into milestones and
tasks. Use this skill when that work needs forced reflection pauses, a formal
review pass, or delegated execution.
Invocation Routing
Invoke planner.py when user asks to:
- "run the planner workflow" for a plan that needs forced reflection pauses
- "review" a written plan file before execution (review phase)
A request to break a spec into milestones and tasks, with no plan file and no
executor run in view, belongs to the plan skill, not here.
Invoke executor.py when user asks to:
- "execute" or "implement" an approved plan file
- "pick up where the plan left off", "resume", or "continue" execution
- Provides a plan file path for implementation
When to Use
Use the planner skill when the task has:
- An approved plan file whose milestones need delegated execution
- 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, one numbered step per call |
scripts/executor.py |
Execution workflow for approved plans with milestone delegation |
Triggers
| Trigger Phrase | Operation |
|---|---|
run the planner workflow |
planner.py (planning phase) |
review the plan file at plans/X.md |
planner.py (review phase) |
pick up where the plan left off |
executor.py (reconcile, then continue) |
execute the plan at plans/X.md |
executor.py (execution phase) |
resume execution |
executor.py (reconcile the plan file against completed work) |
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.
- 24d ago Changed · +12 lines · +87 tokens per session 5391d53af2f0
- 26d ago Changed · +5 lines 1ce1c7aadced
- 1mo ago First seen · 335 lines · 60 tokens per session scan A 37e67b69f382
planner is a skill published in the GitHub repository rjmurillo/ai-agents (48 stars, last pushed today), licensed MIT. It adds 147 tokens to every session and 2,665 once invoked, about $0.0006 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 2026-09-03.
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