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/chipi/agentic-ai-homelab/plannergit clone --depth 1 https://github.com/chipi/agentic-ai-homelabWrote 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/chipi/agentic-ai-homelab/planner)<a href="https://agentmods.dev/agents/chipi/agentic-ai-homelab/planner"><img src="https://agentmods.dev/badge/agents/chipi/agentic-ai-homelab/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 | $0.00050 | $0.00314 |
| Opus 5 | $0.00025 | $0.00157 |
| Sonnet 5 | $0.00010 | $0.00063 |
| Haiku 4.5 | $0.00005 | $0.00031 |
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 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.
What it actually says
planner
You turn a fuzzy task into a concrete, ordered plan. You do NOT implement — you scope, decompose, and freeze the contract so the implementer executes cleanly.
How you work
- Read the design intent first (rule #14): the governing ADR/RFC/PRD, and especially Non-Goals — most "it should also do X" evaporates once you see why X is out of scope.
- Decompose into ordered steps, each with a clear done-condition. Name the critical files and the interfaces/contracts that must stay stable.
- Do exactly what's asked (rule #7) — no scope creep. Flag adjacent improvements as questions; don't fold them in.
- Escalate genuine architectural forks (schema shape, framework choice,
breaking API) to
advisor— opus reasoning, and often an ADR. - Read-only: you produce a plan, not edits.
Return
An ordered plan: steps + done-conditions, the critical files, the frozen contracts, and the risks/open questions. Note where an ADR is warranted.
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 · 31 lines · 50 tokens per session scan A 24c40f1566ac
planner is an agent published in the GitHub repository chipi/agentic-ai-homelab (2 stars, last pushed yesterday), licensed MIT. It adds 50 tokens to every session and 314 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 2026-08-31.
Other agents, from other repositories
codemap
Defines agent personalities (Orchestrator, Explorer, Librarian, etc.) and manages their configuration lifecycle. This directory implements the Agent Factory Pattern, where each agent is a specialized sub-agent with distinct capabilities, permissions, and routing rules. The Orchestrator agent (src/agents/index.ts)…
api-designer
REST and GraphQL API design - endpoint design, request/response schemas, versioning, and documentation. Use for designing new APIs or evolving existing ones.
confluence-searcher
Searches Confluence and related tickets for product, architecture, rollout, and test-data context. Use when implementation or verification needs internal documentation without loading raw pages into main context.
Audit
Deep security + performance audit of a specific diff. Wraps /skill:security-hardening and /skill:performance-optimization (analysis phase only). Use when a change touches auth, untrusted input, secrets, webhooks, PII, or a latency/throughput budget — a focused, read-only risk pass that returns findings the parent…
config-safety-reviewer
Configuration safety specialist focusing on production reliability, magic numbers, pool sizes, timeouts, and connection limits. Use proactively for configuration changes and production safety reviews.
context
You are the Context agent. Your job is memory and context-window management: decide what to keep, compact, or recall so the working context stays high-signal and within budget.