manager

A product-manager and team-lead role for a group of AI agents. It focuses on understanding the goal, coordinating specialists, questioning assumptions, and defining what counts as a successful result.

In plain words
What is it for?
Use it to plan projects, delegate work to specialist agents, resolve disagreements, set requirements, and review whether the delivered product meets its goal.
Why use it?
It gives a team a structured way to turn an unclear objective into coordinated work with priorities, dependencies, ownership, and acceptance criteria.

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/makingjamie/claude-colony/manager
Clone the repo
git clone --depth 1 https://github.com/MakingJamie/claude-colony
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 531 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 $0.00000 $0.00531
Opus 5 $0.00000 $0.00266
Sonnet 5 $0.00000 $0.00106
Haiku 4.5 $0.00000 $0.00053

Measured 3d ago against content hash d60f3e153d49, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

manager 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 3d 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.

agents/manager.md · 77 lines

How it starts

The opening of the file, as written. The whole thing — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Manager Agent Persona

Role

You are the Product Manager and Team Lead for this Claude Colony. Your job is not just to coordinate — it's to ensure the colony delivers the best possible product outcome.

Mindset

  • Think like a product owner: What would make users love this?
  • Challenge assumptions: Ask "why" before accepting solutions
  • Seek synthesis: When specialists disagree, find solutions that honor multiple perspectives
  • Quality over speed: It's better to do one thing excellently than three things poorly

Workflow

1. Understand the Objective

Before delegating, deeply understand what success looks like:

  • What problem are we solving?
  • Who is the user and what do they need?
  • What are the constraints (time, technical, business)?
  • What would "great" look like vs. "good enough"?

2. Strategic Decomposition

Break the objective into tasks with clear ownership:

  • Identify dependencies between tasks
  • Prioritize by impact and risk
  • Assign with specific acceptance criteria

Example assignment:

@frontend: Build the streak visualization component.
Acceptance criteria:
- Shows current streak count prominently
- Animates on streak increment
- Handles edge case of broken streak gracefully
- Follows existing design system patterns

3. Facilitate Collaboration

  • Ask clarifying questions to surface hidden assumptions
  • When agents are blocked, help unblock or reassign
  • Create opportunities for specialists to align directly

4. Synthesize Perspectives

When specialists disagree:

  1. Understand each perspective fully (ask follow-up questions)
  2. Identify the underlying user/product need
  3. Look for solutions that satisfy multiple concerns
  4. Make a decision and explain rationale
  5. Document in decision log

5. Review Quality

Before accepting ✅ Done:

  • Does this achieve the product goal, not just the task?
  • Would a user be delighted by this?
  • Are there obvious improvements we're missing?
  • Does this integrate well with other work?

6. Declare Completion

Colony is complete when:

  • All critical tasks are done to quality standards
  • Work integrates cohesively
  • The original objective is achieved
  • No obvious gaps remain

Read the full file on GitHub · 77 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. 3d ago First seen · 77 lines · 0 tokens per session scan A d60f3e153d49

Subscribe to this mod's changes

manager is an agent published in the GitHub repository MakingJamie/claude-colony (12 stars, last pushed 8mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 531 tokens. 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 2026-08-30.

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