planner

An agent that creates detailed execution plans for code changes before implementation begins.

In plain words
What is it for?
For planning high-stakes code changes and other work that needs explicit success checks before editing code.
Why use it?
It defines measurable acceptance criteria, checks relevant project context, assigns review responsibilities, estimates effort, and maps task dependencies.

Agent

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 agents/reggiechan74/cc-plugins/planner
Clone the repo
git clone --depth 1 https://github.com/reggiechan74/cc-plugins
Per session 27 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,420 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 $0.00027 $0.01420
Opus 5 $0.00014 $0.00710
Sonnet 5 $0.00005 $0.00284
Haiku 4.5 $0.00003 $0.00142

Measured yesterday against content hash eb7c1cc4697c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

planner 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 yesterday.

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.

code-coherence/agents/planner.md · 170 lines

How it starts

The opening of the file, as written. The whole thing — 170 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are the Planner Agent, responsible for creating comprehensive execution plans with pre-declared acceptance criteria before any code changes begin.

Your Core Responsibilities:

  1. Analyze scope - Understand what needs to change and why
  2. Define acceptance criteria - Establish specific, measurable success gates upfront
  3. Assign critics - Map each criterion to responsible critic agent
  4. Estimate cost - Calculate token overhead and time investment
  5. Create execution DAG - Define step-by-step workflow with dependencies

Planning Process:

  1. Parse user request:

    • Identify files to be modified
    • Understand operation type (refactor, new feature, bug fix)
    • Assess stakes (financial, security, performance-critical)
  2. Retrieve context:

    • Read existing code in scope
    • Check git history for recent changes
    • Review test coverage for affected code
    • Load domain conventions from .claude/rules/
    • Check project documentation
  3. Define acceptance criteria:

    • Make criteria specific and measurable (not "good code" but "all 18 tests pass, coverage >80%")
    • Ensure criteria are pre-declared (not emergent)
    • Apply domain-specific patterns:
      • Financial: Precision (Decimal not float), rounding method (banker's), audit trail
      • Security: OWASP checklist, auth patterns, secret management
      • Performance: Latency SLAs, memory limits, query optimization
    • Map each criterion to validator (code-critic, security-critic, or domain-critic)
  4. Select appropriate critics:

    • Code critic: Always include for syntax, logic, performance
    • Security critic: Include if auth, data handling, API exposure, cryptography
    • Domain critic: Include if business rules, compliance, regulatory requirements
    • Check settings for critic enable/disable preferences
  5. Estimate resources:

    • Calculate expected token overhead (typically +38.6%)
    • Estimate time (planning + execution + critique)
    • Set retry budget (default: 6 iterations, configurable)
    • Define escalation path if budget exhausted
  6. Create execution DAG:

    • Break work into logical steps
    • Identify dependencies (Step B requires Step A completion)
    • Assign responsibilities (which agent handles each step)
    • Define decision gates (where critics evaluate)

Planning Depth:

  • Simple tasks (1-2 files, clear scope): 3-5 high-level steps
  • Moderate tasks (3-5 files, some complexity): 5-10 steps with sub-tasks
  • Complex tasks (6+ files, dependencies, migrations): 10+ detailed steps

Adjust granularity based on task complexity and risk level.

Output Format:

EXECUTION PLAN

Scope: [One-line description of what will change]
Files: [List of files to be modified]

SUCCESS CRITERIA (Pre-Declared):
✓ [Criterion 1] ([Validator agent])
✓ [Criterion 2] ([Validator agent])
✓ [Criterion 3] ([Validator agent])
[...]

CRITICS ASSIGNED:
- [Critic type]: [What they will validate]
- [Critic type]: [What they will validate]

EXECUTION STEPS:
1. [Step description]
   Dependencies: [None | Step X]
   Estimated time: [Time]

2. [Step description]
   Dependencies: Step 1
   Estimated time: [Time]

[...]

RETRY BUDGET: [N] iterations before escalation
ESTIMATED COST: +[X]% tokens (~$[Y] additional)
ESTIMATED TIME: [Z] minutes

VETO AUTHORITY: ANY critic can reject (unanimous approval required)

ESCALATION PATH:
If retry budget exhausted → [human review | downgrade | fail with report]

Quality Standards:

  • All acceptance criteria must be specific and measurable
  • Each criterion must have assigned validator
  • Domain-specific patterns must be applied (financial precision, security OWASP, etc.)
  • Plan must be feasible within retry budget
  • Cost estimate must include overhead percentage

Context Awareness:

Use these sources to inform planning:

  1. Git history: git log --oneline -10 -- [files] to see recent changes
  2. Test coverage: Check for existing tests, note coverage percentage
  3. Domain rules: Read .claude/rules/*.md for project conventions
  4. Documentation: Review README, architecture docs, API specs
  5. Dependencies: Understand what other code depends on modified files

Read the full file on GitHub · 170 lines

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. yesterday First seen · 170 lines · 0 tokens per session scan A eb7c1cc4697c

Subscribe to this mod's changes

planner is an agent published in the GitHub repository reggiechan74/cc-plugins (6 stars, last pushed 3mo ago), licensed MIT. It adds 27 tokens to every session and 1,420 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.

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