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 skills/hyperb1iss/hyperskills/plannpx skills add hyperb1iss/hyperskills --skill plangit clone --depth 1 https://github.com/hyperb1iss/hyperskillsWrote 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/hyperb1iss/hyperskills/plan)<a href="https://agentmods.dev/skills/hyperb1iss/hyperskills/plan"><img src="https://agentmods.dev/badge/skills/hyperb1iss/hyperskills/plan.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 | $0.00058 | $0.03430 |
| Opus 5 | $0.00029 | $0.01715 |
| Sonnet 5 | $0.00012 | $0.00686 |
| Haiku 4.5 | $0.00006 | $0.00343 |
Grade A, and why
plan 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 4d 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 — 250 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Structured Planning
Verification-driven task decomposition with Sibyl-native tracking. Mined from 200+ real planning sessions: the plans that actually survived contact with code.
Core insight: Plans fail when steps can't be verified. Decomposition that lands in concrete checks survives contact with reality; abstract bullets don't. And a plan is a durable artifact consumed by autonomous runs and other agents, not chat exhaust. Tracking in Sibyl and the repo lets it outlive the context window that produced it.
How to read this skill: the first plan is a hypothesis, and replanning is the rule rather than evidence the plan was bad. The Phase 1 scale table is the real dial. It decides whether you plan at all.
The shape: SCOPE → EXPLORE → DECOMPOSE → VERIFY & APPROVE → TRACK, with a loop back to DECOMPOSE when review finds gaps.
Phase 1: SCOPE
Bound the work before decomposing it. The goal is calibrating planning depth to actual scope, not generating a deliverable.
Common moves
-
Search Sibyl for related tasks, decisions, and prior plans:
sibyl search "<feature keywords>",sibyl task list -s todo. Quick, and it often surfaces an already-decomposed predecessor. -
Define success criteria in measurable terms ("tests pass", "endpoint returns X", "p95 latency < 200ms") instead of vague goals like "improve performance".
-
Write completion criteria an autonomous run can consume: complete AND validated (what proves each wave, plus review gates at wave checkpoints when stakes warrant). A run that can't close every gate ends blocked with receipts and a runbook for the remaining gates; blocked-cleanly is a legitimate terminal state, fake-done is not.
-
Identify constraints: files that shouldn't change, dependencies to respect, timeline or budget pressure.
-
Calibrate planning depth to scope:
Scale Description Planning depth Quick fix < 3 files, clear solution Skip planning, go build Feature 3-10 files, known patterns Light plan (this skill) Epic 10+ files, new patterns Full plan + orchestration Redesign Architecture change Full plan + research first
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.
- 4d ago First seen · 250 lines · 58 tokens per session scan A 7829071c2255
plan is a skill published in the GitHub repository hyperb1iss/hyperskills (31 stars, last pushed 8d ago), licensed MIT. It adds 58 tokens to every session and 3,430 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.
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