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/event4u-app/agent-config/complexity-first-planningnpx skills add event4u-app/agent-config --skill complexity-first-planninggit clone --depth 1 https://github.com/event4u-app/agent-configWrote 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/event4u-app/agent-config/complexity-first-planning)<a href="https://agentmods.dev/skills/event4u-app/agent-config/complexity-first-planning"><img src="https://agentmods.dev/badge/skills/event4u-app/agent-config/complexity-first-planning.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 | $0.00032 | $0.01027 |
| Opus 5 | $0.00016 | $0.00513 |
| Sonnet 5 | $0.00006 | $0.00205 |
| Haiku 4.5 | $0.00003 | $0.00103 |
Grade A, and why
complexity-first-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 6d 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 — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
complexity-first-planning
Part of the Reasoning Discipline Protocol. Engage per
rdp-gate (skip on trivial / linear
tasks; light touch on a strong-reasoning host).
Provenance. This is an RDP derivation from general engineering discipline (risk-first / critical-path / pre-mortem) — it is not an Anthropic- documented Fable behavior. Fable's "start at the top of your difficulty range" is about task selection (give the model harder tasks), not intra-task order. The skill stands on its own merit; it is not sold as a frontier-model transplant.
When to use
- Staging multi-component work where the hardest/most-uncertain part is not yet proven.
- A plan whose later steps depend on an assumption that could collapse.
Do NOT use for single-step, linear, or fully-specified tasks (no load-bearing unknown to resolve), or when the user has already fixed the sequence.
When the agent should load this
- The user asks to "plan", "break down", or "stage" work that spans ≥2 components and at least one part is unproven.
- A multi-step plan is forming whose later steps assume something untested.
- Mid-task: a step just failed because an earlier, easier step baked in a wrong assumption — reload this and re-sequence risk-first.
Procedure
- Inspect and name the unknowns. Read the affected components first (start from the repo slot of the context-spine when present), then list which carry real uncertainty (technical feasibility, an unverified integration, an ambiguous requirement) — analyze the existing system before planning any change.
- Assess and rank by load-bearing risk. The load-bearing unknown is the one whose failure invalidates the most dependent work — not the one that is merely hard.
- Resolve it first. Spike / probe / prototype the load-bearing unknown
before building anything that depends on it. Record the result in the notes
file (see
notes-first-reasoning): prediction → result → lesson. - Cascade. Once the riskiest assumption holds (or is corrected), sequence the dependent work. If it fails, the cheap early failure saved the rework.
What ships with it
1 file 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.
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.
- 6d ago First seen · 98 lines · 32 tokens per session scan A cbc4afc36e37
complexity-first-planning is a skill published in the GitHub repository event4u-app/agent-config (10 stars, last pushed today), licensed MIT. It adds 32 tokens to every session and 1,027 once invoked, about $0.0002 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.
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