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 megamen32/LastHumanCommit --skill planninggit clone --depth 1 https://github.com/megamen32/LastHumanCommitWrote 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/megamen32/lasthumancommit/planning)<a href="https://agentmods.dev/skills/megamen32/lasthumancommit/planning"><img src="https://agentmods.dev/badge/skills/megamen32/lasthumancommit/planning/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/megamen32/lasthumancommit/planning"><img src="https://agentmods.dev/badge/skills/megamen32/lasthumancommit/planning.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 | $0.00020 | $0.00629 |
| Opus 5.5 | $0.00008 | $0.00252 |
| Sonnet 5.5 | $0.00004 | $0.00126 |
| Haiku 4.5 | $0.00002 | $0.00063 |
Grade A, and why
planning 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 yesterday.
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 — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Planning
Use only when planning can materially reduce wrong-path or coordination cost.
Three-pass design
When choosing a design, use working solution -> ideal version -> 80%-value MVP
even when there is only one practical approach. The architecture-design skill owns
the detailed method. An obvious tiny fix needs only a short pass, not a new form.
The 80% target concerns useful value, never incomplete implementation or silently
missing mandatory requirements.
Procedure
Begin with current user inputs, project state and applicable verified product
and LHC learning from existing indexes. Verify freshness and use prior results
before redesign. Use $architecture-design for architectural decisions, risky
assumptions and the end-to-end path before substantial implementation.
- Record the latest business outcome and accepted MVP Definition of Done.
- Trace the actual production consumer path.
- State the shortest real canary and cheapest sufficient proof.
- Rank direct Lead work and delegation by wall-clock, scarce quota, handoff, retry, human interruption, and wrong-path cost.
- Load
$task-decompositionand$decompose-and-dispatchwhen parallel or multi-cycle work remains. Use$model-routingfor actual model selection; hard decisions use the strongest suitable model before bounded execution. - Treat every 20 active minutes as a progress and route checkpoint, not an agent lifetime limit.
- Give every declared work cycle an immutable minimum/maximum estimate and run the business time guard at observable checkpoints; report every crossed hour and original-maximum overrun. Derive that range from per-leaf work/proof and specific uncertainty. Show available slots and actual parallel dispatch; sum effort separately from capacity-respecting critical-path duration, with joins/testing/waits explicit. Twenty minutes is a checkpoint, not a task size; no unexplained doubled buffer.
- Obtain the initial independent Overseer audit. Full includes coherent technical review and a fresh independent Tester; extra governance needs concrete risk-reduction value. Routine technical choices belong to Lead.
- When a human route choice is useful, present exactly two genuinely different
approaches. For each, use
working solution -> ideal version -> 80%-value MVP: establish how it works, improve that design, then keep the smallest complete version with roughly 80% of the useful result. Implement that third version; state its retained value, deferred scope, cost and real acceptance check. This is one design sequence, not three builds or approval rounds. If the user requests the reasoning behind the plan, show the three passes in one plan.
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.
- yesterday Changed · +10 lines bdad1a3d8c25
- 1mo ago Changed · +12 lines 67e95e518f8e
- 1mo ago First seen · 37 lines · 20 tokens per session scan A 5e8087e2744a
planning is a skill published in the GitHub repository megamen32/LastHumanCommit (2 stars, last pushed yesterday), licensed MIT. It adds 20 tokens to every session and 629 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.
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