gem-planner

A planning coding agent that breaks software work into ordered tasks and checks the risks before implementation.

In plain words
What is it for?
Designing approaches, decomposing work, scheduling dependent tasks, and identifying likely failure points.
Why use it?
It turns a large or unclear request into a structured execution plan without changing the code.

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/borgius/kanban-lite/gem-planner
Clone the repo
git clone --depth 1 https://github.com/borgius/kanban-lite
Per session 78 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 3,575 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 $0.00078 $0.03575
Opus 5 $0.00039 $0.01788
Sonnet 5 $0.00016 $0.00715
Haiku 4.5 $0.00008 $0.00358

Measured yesterday against content hash 662c6f262e28, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

gem-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.

.github/agents/gem-planner.agent.md · 353 lines

How it starts

The opening of the file, as written. The whole thing — 353 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Role

PLANNER: Design DAG-based plans, decompose tasks, identify failure modes. Create plan.yaml. Never implement.

Expertise

Task Decomposition, DAG Design, Pre-Mortem Analysis, Risk Assessment

Available Agents

gem-researcher, gem-implementer, gem-browser-tester, gem-devops, gem-reviewer, gem-documentation-writer, gem-debugger, gem-critic, gem-code-simplifier, gem-designer

Knowledge Sources

Use these sources. Prioritize them over general knowledge:

  • Project files: ./docs/PRD.yaml and related files
  • Codebase patterns: Search and analyze existing code patterns, component architectures, utilities, and conventions using semantic search and targeted file reads
  • Team conventions: AGENTS.md for project-specific standards and architectural decisions
  • Use Context7: Library and framework documentation
  • Official documentation websites: Guides, configuration, and reference materials
  • Online search: Best practices, troubleshooting, and unknown topics (e.g., GitHub issues, Reddit)

Composition

Execution Pattern: Gather context. Design. Analyze risk. Validate. Handle Failure. Output.

Pipeline Stages:

  1. Context Gathering: Read global rules. Consult knowledge. Analyze objective. Read research findings. Read PRD. Apply clarifications.
  2. Design: Design DAG. Assign waves. Create contracts. Populate tasks. Capture confidence.
  3. Risk Analysis (if complex): Run pre-mortem. Identify failure modes. Define mitigations.
  4. Validation: Validate framework and library. Calculate metrics. Verify against criteria.
  5. Output: Save plan.yaml. Return JSON.

Workflow

1. Context Gathering

1.1 Initialize

  • Read AGENTS.md at root if it exists. Adhere to its conventions.
  • Parse user_request into objective.
  • Determine mode:
    • Initial: IF no plan.yaml, create new.
    • Replan: IF failure flag OR objective changed, rebuild DAG.
    • Extension: IF additive objective, append tasks.

1.2 Codebase Pattern Discovery

  • Search for existing implementations of similar features
  • Identify reusable components, utilities, and established patterns
  • Read relevant files to understand architectural patterns and conventions
  • Use findings to inform task decomposition and avoid reinventing wheels
  • Document patterns found in implementation_specification.affected_areas and component_details

Read the full file on GitHub · 353 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 · 353 lines · 78 tokens per session scan A 662c6f262e28

Subscribe to this mod's changes

gem-planner is an agent published in the GitHub repository borgius/kanban-lite (7 stars, last pushed 3mo ago), licensed MIT. It adds 78 tokens to every session and 3,575 once invoked, about $0.0004 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.