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/danweinerdev/claude-sdd-planner/plannpx skills add danweinerdev/claude-sdd-planner --skill plangit clone --depth 1 https://github.com/danweinerdev/claude-sdd-plannerWrote 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/danweinerdev/claude-sdd-planner/plan)<a href="https://agentmods.dev/skills/danweinerdev/claude-sdd-planner/plan"><img src="https://agentmods.dev/badge/skills/danweinerdev/claude-sdd-planner/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 | $0.00079 | $0.02546 |
| Opus 5 | $0.00039 | $0.01273 |
| Sonnet 5 | $0.00016 | $0.00509 |
| Haiku 4.5 | $0.00008 | $0.00255 |
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 today.
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.
This is a copy
92% identical to sdd-plan — 17 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/plan — Decompose Work into an Executable Plan Graph
Path Resolution
The plugin directory contains commands/, agents/, and shared/ as siblings. Find it by globbing for **/commands/research/SKILL.md in both the current directory and ~/.claude/plugins/cache/; if multiple versions match, sort them as semantic versions (like sort -V) and use the highest, then strip commands/research/SKILL.md from the match. Resolve the planning root (artifacts) and target repository per shared/path-resolution.md in the plugin directory.
What This Skill Does
Three tasks are LLM-shaped, and this skill does exactly those three: negotiate intent (the interview), decompose (author the node payload), and read back diagnostics (compile findings, silhouette, critical path). Everything else — validation, coverage checking, view rendering, state — is a CLI call, and the tool refuses what a narrated plan used to let drift. You never write plan or phase markdown by hand under this protocol: phase docs are rendered projections of the committed graph, regenerated by sdd compile, and hand edits to them are overwritten or refused.
Routing: Graph Plans vs v1 Plans
Route by graph presence, not by preference:
Plans/<Name>/<Name>-Graph.jsonexists → this protocol, in extend/revise mode (new nodes arrive as proposal payloads; the graph is the source of truth).- The plan exists without a graph → it is a v1 markdown plan and continues under the v1 conventions until converted (D-0022's v1 clause): its statuses, completion evidence, and phase reviews keep their existing rules from
shared/frontmatter-schema.mdandshared/completion-evidence.md. Make conservative, id-preserving edits only. When the user wants graph execution, offersdd graph convert --plan <Name>— conversion emits blocking sentinels (untriagedhazards,unspecifiedgates,NEEDS-CONTRACTcontracts) that are real judgments to resolve through the payload path, never defaults to accept. - New plan → this protocol from the start.
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.
- today Changed · -50 lines · -5 tokens per session 8dcfde5072ad
- 4d ago First seen · 163 lines · 84 tokens per session scan A d9253c090fc8
plan is a skill published in the GitHub repository danweinerdev/claude-sdd-planner (2 stars, last pushed yesterday), licensed MIT. It adds 79 tokens to every session and 2,546 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to sdd-plan, differing in 17 lines, and is treated as a copy.
Other skills, from other repositories
hns-lsel-curator
Local Self-Evolution Loop (LSEL) curator — the CLUSTER + drain engine for the GOOS-local PROPOSE→APPLY seam closure (SPEC-LSEL-LOCAL-EVOLUTION-001). Companion-offset drain of .moai/lessons-inbox.jsonl with a drain-side severity filter that drops the 65% Bash-timeout/sandbox noise, eventkey clustering with a frequency…
moai-workflow-worktree
Git worktree management for parallel SPEC development with isolated workspaces, automatic branch registration, and seamless MoAI-ADK integration. Use when setting up parallel development environments.
hns-workflow-ci-loop
Unified CI watch + auto-fix loop skill. Polls gh pr checks after /moai sync PR creation, classifies required vs auxiliary failures, attempts safe automated patches (max 3 iterations), and escalates semantic failures to the user. Use for CI loop workflow — NOT for general loop iteration patterns (see…
moai-kanban-foreman
One unattended kanban foreman iteration: watch the backlog queue, dispatch the next operator-picked card to an isolated worker, collect completion evidence on read (not on claims), and report. This is the body the project's loop.md driver invokes each iteration of a bare /loop; it can also be invoked directly to test…
hns-moaiadk-patterns
Skill "hns-moaiadk-patterns" from modu-ai/moai-adk, covering moai-adk-go domain patterns, architecture quick reference, key source paths, pipeline specialist delegation map and template-first build cycle.
moai-harness-learner
Harness learning subsystem coordinator. Produces Tier 4 auto-update proposal payloads consumed by the orchestrator (which surfaces them via AskUserQuestion) and orchestrates Apply/Rollback flows. Triggers when harness learning proposals are pending or learning lifecycle management is needed.