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 commands/skullninja/coco-workflow/planning-sessiongit clone --depth 1 https://github.com/skullninja/coco-workflowWhat 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 | $0.00027 | $0.00946 |
| Opus 5 | $0.00014 | $0.00473 |
| Sonnet 5 | $0.00005 | $0.00189 |
| Haiku 4.5 | $0.00003 | $0.00095 |
Grade A, and why
planning-session 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 2d 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 — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Planning Session
Guide the user through a structured planning session.
Determine Session Type
$ARGUMENTS may specify the type. If not, ask using AskUserQuestion.
Types:
- strategic -- Roadmap review and prioritization
- tactical -- Plan a specific feature (interview -> design -> tasks -> import)
- operational -- Status check and task prioritization
- triage -- Quick-score a bug, feature request, or feedback item
Process
Strategic
- Review project goals and metrics
- Audit existing roadmap/feature list
- Prioritize features by impact
- For topics needing deep investigation before creating analysis docs, offer to use the
interviewskill to gather structured context. This produces a discovery brief that can inform the analysis. - Update roadmap and issue tracker projects
- Save notes to
docs/planning-sessions/YYYY-QN.md - For each analysis topic discussed, offer to save it as a standalone analysis doc:
- Read
discovery.analysis_dirfrom.coco/config.yaml(default:docs/analysis) - Load analysis template from
.coco/templates/analysis-template.mdif it exists, otherwise use${CLAUDE_PLUGIN_ROOT}/templates/analysis-template.md - Fill in findings, implications, and recommendations from the session discussion
- Write to
{discovery.analysis_dir}/{topic-slug}.md - These analysis docs are discoverable by
/coco:roadmapfor roadmap generation
- Read
Tactical
Step 1: Determine Complexity Tier
Before running the pipeline, classify the feature scope:
| Tier | Signal | Pipeline |
|---|---|---|
| Trivial | User says "small", "quick", "hotfix"; single file mentioned; bug fix | hotfix skill (no epic) |
| Light | 1-3 files, single user story, no internal dependencies | design (light mode) -> import (design-only) |
| Standard | Multi-file, multiple stories, dependencies between components | interview -> design -> tasks -> import |
Ask the user using AskUserQuestion: "How complex is this feature?" with options:
- Quick fix -- Single issue, 1 file (routes to Trivial)
- Small feature -- 1-3 files, straightforward (routes to Light)
- Full feature -- Multiple files, dependencies, needs detailed planning (routes to Standard)
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.
- 2d ago First seen · 87 lines · 27 tokens per session scan A 3f10975e521e
planning-session is a command published in the GitHub repository skullninja/coco-workflow (7 stars, last pushed 2d ago), licensed MIT. It adds 27 tokens to every session and 946 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 commands, from other repositories
super-dev
Command "super-dev" from shangyankeji/super-dev, covering /super-dev (claude-code), 输入, super dev runtime contract, local knowledge contract and 首轮响应契约（首次触发必须执行）.
validate
You are the quality gate. Your job is to verify that a phase's implementation meets quality standards before the team moves to the next phase. No phase should advance until validation passes.
implement
You are the phase dispatcher. Your job is to route implementation work to the correct phase agent with the right context.
progress
You are generating a visual progress report showing which phases are complete, in-progress, or pending for the current feature.
commit
You are creating a conventional commit scoped to the current phase of work.
prd
You are generating a Product Requirements Document (PRD) for the project described below.