planning-triage

planning-triage is a command for coding agents from skullninja/coco-workflow. It costs 24 tokens per session (577 once invoked), scanned A, original, MIT.

A quick scoring workflow for deciding what to do with a bug, enhancement, feature request, or feedback item. It rates user impact, urgency, and effort, then recommends immediate action, backlog, or deferral.

In plain words
What is it for?
Use it to triage incoming work, explain why an item should be prioritized, and create an issue when the result calls for action.
Why use it?
It provides a consistent way to compare requests instead of relying only on intuition. Approved items can be turned into issues.

Command

Part of the coco plugin — 6 skills, 14 commands, 4 agents, 3 hooks shipped together

Install

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.

agentmods
npx agentmods add commands/skullninja/coco-workflow/planning-triage
Clone the repo
git clone --depth 1 https://github.com/skullninja/coco-workflow

Or install coco, the plugin that ships this one along with the rest of its 6 skills, 14 commands, 4 agents, 3 hooks.

Wrote 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.

agentmods badge for planning-triage

README.md
[![agentmods](https://agentmods.dev/badge/commands/skullninja/coco-workflow/planning-triage.svg)](https://agentmods.dev/commands/skullninja/coco-workflow/planning-triage)
Your own site
<a href="https://agentmods.dev/commands/skullninja/coco-workflow/planning-triage"><img src="https://agentmods.dev/badge/commands/skullninja/coco-workflow/planning-triage.svg" alt="Measured on agentmods" height="20"></a>
Per session 24 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 577 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00024 $0.00577
Opus 5 $0.00012 $0.00289
Sonnet 5 $0.00005 $0.00115
Haiku 4.5 $0.00002 $0.00058

Measured 5d ago against content hash 6fc49fcf2931, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

planning-triage 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 5d 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.

commands/planning-triage.md · 87 lines

What it actually says

Planning Triage

Quick-score an item and determine its disposition.

Input

$ARGUMENTS

The item to triage (bug report, feature request, user feedback, competitor feature).

Process

1. Understand the Item

Parse the input to identify:

  • Type: Bug, Feature, Enhancement, Competitive Response
  • Description: What is being requested or reported
  • Context: Why it matters (user impact, competitive pressure, etc.)

2. Score

Apply the impact-first scoring framework:

Score = (Impact + Urgency) / Effort
Factor 1 2 3 4 5
Impact No effect on users Minor convenience Moderate engagement Significant daily value Critical for adoption/retention
Urgency Someday/nice-to-have Next quarter This month This week Today/blocking
Effort Multi-week project ~1 week ~2-3 days ~hours ~minutes

3. Rate Each Factor

For each factor, provide the score (1-5) and brief justification.

4. Calculate and Interpret

Score = (Impact + Urgency) / Effort

>= 3.0 -> IMMEDIATE ACTION
1.5-3.0 -> BACKLOG
< 1.5  -> DEFER

5. Disposition

If IMMEDIATE (>= 3.0):

  • Create issue with High/Urgent priority (based on issue_tracker.provider in config)
  • If feature: recommend /coco:planning-session tactical
  • If bug: recommend creating hotfix branch

If BACKLOG (1.5-3.0):

  • Create issue with Normal priority
  • Tag for next operational planning session

If DEFER (< 1.5):

  • Document the rationale
  • Do NOT create an issue
  • Note for quarterly strategic review

6. Output

## Triage: {item title}

**Type:** {Bug/Feature/Enhancement}
**Score:** {X.X}

| Factor | Score | Rationale |
|--------|-------|-----------|
| Impact | {N} | {reason} |
| Urgency | {N} | {reason} |
| Effort | {N} | {reason} |

**Disposition:** {IMMEDIATE / BACKLOG / DEFER}
**Action:** {what was done}
Changes

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.

  1. 5d ago First seen · 87 lines · 24 tokens per session scan A 6fc49fcf2931

Subscribe to this mod's changes

planning-triage is a command published in the GitHub repository skullninja/coco-workflow (7 stars, last pushed 5d ago), licensed MIT. It adds 24 tokens to every session and 577 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.