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/captainme-ai/lead-dev-os/step2-scope-tasksnpx skills add CaptainMe-AI/lead-dev-os --skill step2-scope-tasksgit clone --depth 1 https://github.com/CaptainMe-AI/lead-dev-osWrote 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/captainme-ai/lead-dev-os/step2-scope-tasks)<a href="https://agentmods.dev/skills/captainme-ai/lead-dev-os/step2-scope-tasks"><img src="https://agentmods.dev/badge/skills/captainme-ai/lead-dev-os/step2-scope-tasks.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 | $0.00020 | $0.03238 |
| Opus 5 | $0.00010 | $0.01619 |
| Sonnet 5 | $0.00004 | $0.00648 |
| Haiku 4.5 | $0.00002 | $0.00324 |
Grade A, and why
step2-scope-tasks 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 — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Step 2: Scope Tasks
Break a specification into ordered task groups with explicit context-awareness directives.
Phases 1–2 are read-only research; plan mode is optional. If invoked in plan mode, present the task-group outline (groups, dependencies, grouping strategy) as the plan, and write tasks.md after the user approves and plan mode exits — file writes are blocked while plan mode is active.
Instructions
You are a senior engineer breaking down a spec into implementable task groups. Each group is an atomic, focused unit of work — a vertical slice of the feature or a stack layer, per the grouping strategy chosen in Phase 2 — with hierarchical numbered subtasks. Every task group MUST include explicit directives to read and update context files.
Every task group MUST also stand on its own as a complete user story — a non-technical stakeholder who understands the feature's goal should be able to read the group and know (a) what value it delivers and (b) what "done" looks like, without reading any code or technical acceptance criteria.
This skill does not write code or implementation plans — it produces tasks.md only; execution and per-group planning belong to /lead-dev-os:step3-implement-tasks.
Phase 1: Load Context
-
Find the spec folder. Look for the most recent
lead-dev-os/specs/YYYY-MM-DD-*/folder, or ask the user which spec to work from. -
Read
spec.mdfrom the spec folder. -
Read
planning/requirements.mdfor additional context. -
Read
agents-context/README.md— use this index to identify which concept and standard files are relevant to this spec. Load only what you need for the current feature, not everything. -
Read the relevant concept and standard files identified from the README — understand domain knowledge, established patterns, and project conventions that apply to this feature.
-
Analyze the existing codebase — via research subagents, not in this conversation. A broad codebase scan in the main context crowds out the spec and concept files you just loaded. Dispatch 1–3 read-only research subagents (prefer the
Exploreagent type; fall back togeneral-purpose) in a single parallel batch. Split by area when the feature spans several (e.g. one for backend, one for frontend). Give each a bounded prompt of this shape:
What ships with it
2 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.
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 · 178 lines · 20 tokens per session scan A e4f7d8ca5220
step2-scope-tasks is a skill published in the GitHub repository CaptainMe-AI/lead-dev-os (2 stars, last pushed 15d ago), licensed MIT. It adds 20 tokens to every session and 3,238 once invoked, about $0.0001 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 skills, from other repositories
evolution-auditor
Run a structured organizational design health check — operationalizing the governance learning loop and decision ledger by collecting operational evidence, measuring gate effectiveness, detecting genome drift, and producing an evolution audit with routed recommendations saved to $HOME/.ai-first-kit/. Maintains the…
ai-first-kit
Navigate organizational redesign for AI with a structured 13-skill toolkit that produces persistent artifacts in $HOME/.ai-first-kit/. Routes founders and leaders to the right specialist skill — coordination audit, organizational genome, specification writing, quality gates, governance, role design, political…
nci-manipulation-analysis
Use when asked to analyze content for manipulation, propaganda, disinformation patterns, or when user provides a URL or text asking "is this manipulative?", "analyze this for bias", "check for propaganda", or similar requests. Detects emotional manipulation, suspicious timing, uniform messaging, tribal division, and…
evidence-ledger
Record every material claim as a row in 00-control/evidence-ledger.md carrying a source-authority level and a claim state (verified, corroborated, reported, inferred, unknown, not applicable), and keep observed, interpreted, unknown, and recommended content in visibly separate blocks. Use when inventorying sources…
holdout-validation
Cross-reference agent self-review claims against actual file state using hidden holdout scenarios, producing mapped P1/P2/P3 findings that reference visible acceptance criteria only. Use when verifying implementation completeness after self-review in start (Phase 4 VERIFY), address (convergence check), or review…
runtime-verification
Verify code works at runtime through build verification (mandatory), LSP diagnostics, ad-hoc verification for projects without frameworks, E2E and smoke tests, and visual verification (screenshot-analyze-verify for UI changes). Skip whitelist strictly enforced (markdown-only, config-only, dependency-bump-only with…