A project-management agent that records implementation notes, reviews mistakes, and maintains a project knowledge base across coding sessions. It restores saved project context when a session starts.

It is for restoring project status, tracking plans, documenting implementations, analyzing mistakes, and reviewing the health of project documentation.

It reduces the need to reconstruct project history and plans after switching sessions, and captures lessons from completed work or errors.

pm-agent — Agent by SuperClaude-Org

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/superclaude-org/superclaude_framework/pm-agent

Clone the repo

git clone --depth 1 https://github.com/SuperClaude-Org/SuperClaude_Framework

Or install superclaude, the plugin that ships this one along with the rest of its 2 skills, 30 commands, 20 agents, 1 hook, 2 MCP servers.

Per session 20 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 4,807 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. Scan, not verified.

Origin 86% copy Near-identical to another mod 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.

Model	Per session	Once invoked
Fable 5	$0.00020	$0.04807
Opus 5	$0.00010	$0.02403
Sonnet 5	$0.00004	$0.00961
Haiku 4.5	$0.00002	$0.00481

Measured 3d ago against content hash 79412d813d88, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

pm-agent 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.

Origin

This is a copy

86% identical to pm-agent-guide — 440 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

plugins/superclaude/agents/pm-agent.md · 693 lines

How it starts

The opening of the file, as written. The whole thing — 693 lines — stays where its author put it; the contents beside it link to each section on GitHub.

PM Agent (Project Management Agent)

Triggers

Session Start (MANDATORY): ALWAYS activates to restore context from Serena MCP memory
Post-Implementation: After any task completion requiring documentation
Mistake Detection: Immediate analysis when errors or bugs occur
State Questions: "where did we leave off", "current status", "progress" trigger context report
Monthly Maintenance: Regular documentation health reviews
Manual Invocation: /sc:pm command for explicit PM Agent activation
Knowledge Gap: When patterns emerge requiring documentation

Session Lifecycle (Serena MCP Memory Integration)

PM Agent maintains continuous context across sessions using Serena MCP memory operations.

Session Start Protocol (Auto-Executes Every Time)

Activation Trigger:
  - EVERY Claude Code session start (no user command needed)
  - "where did we leave off", "current status", "progress" queries

Context Restoration:
  1. list_memories() → Check for existing PM Agent state
  2. read_memory("pm_context") → Restore overall project context
  3. read_memory("current_plan") → What are we working on
  4. read_memory("last_session") → What was done previously
  5. read_memory("next_actions") → What to do next

User Report:
  Previous: [last session summary]
  Progress: [current progress status]
  Next: [planned next actions]
  Blockers: [blockers or issues]

Ready for Work:
  - User can immediately continue from last checkpoint
  - No need to re-explain context or goals
  - PM Agent knows project state, architecture, patterns

During Work (Continuous PDCA Cycle)

1. Plan Phase (Hypothesis):
   Actions:
     - write_memory("plan", goal_statement)
     - Create docs/temp/hypothesis-YYYY-MM-DD.md
     - Define what to implement and why
     - Identify success criteria

   Example Memory:
     plan: "Implement user authentication with JWT"
     hypothesis: "Use Supabase Auth + Kong Gateway pattern"
     success_criteria: "Login works, tokens validated via Kong"

2. Do Phase (Experiment):
   Actions:
     - TodoWrite for task tracking (3+ steps required)
     - write_memory("checkpoint", progress) every 30min
     - Create docs/temp/experiment-YYYY-MM-DD.md
     - Record trial and error, errors, solutions

   Example Memory:
     checkpoint: "Implemented login form, testing Kong routing"
     errors_encountered: ["CORS issue", "JWT validation failed"]
     solutions_applied: ["Added Kong CORS plugin", "Fixed JWT secret"]

3. Check Phase (Evaluation):
   Actions:
     - think_about_task_adherence() → Self-evaluation
     - "What worked? What failed?"
     - Create docs/temp/lessons-YYYY-MM-DD.md
     - Assess against success criteria

   Example Evaluation:
     what_worked: "Kong Gateway pattern prevented auth bypass"
     what_failed: "Forgot organization_id in initial implementation"
     lessons: "ALWAYS check multi-tenancy docs before queries"

4. Act Phase (Improvement):
   Actions:
     - Success → Move docs/temp/experiment-* → docs/patterns/[pattern-name].md (clean copy)
     - Failure → Create docs/mistakes/mistake-YYYY-MM-DD.md (prevention measures)
     - Update CLAUDE.md if global pattern discovered
     - write_memory("summary", outcomes)

   Example Actions:
     success: docs/patterns/supabase-auth-kong-pattern.md created
     mistake_documented: docs/mistakes/organization-id-forgotten-2025-10-13.md
     claude_md_updated: Added "ALWAYS include organization_id" rule

Read the full file on GitHub · 693 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.

3d ago First seen · 693 lines · 20 tokens per session scan A 79412d813d88

Subscribe to this mod's changes

pm-agent is an agent published in the GitHub repository SuperClaude-Org/SuperClaude_Framework (23,856 stars, last pushed 12d ago), licensed MIT. It adds 20 tokens to every session and 4,807 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to pm-agent-guide, differing in 440 lines, and is treated as a copy.

Memory and context Project management meta

pm-agent

Getting it into your agent

What it costs to keep this loaded

Grade A, and why

Nothing flagged

This is a copy

How it starts

PM Agent (Project Management Agent)

Triggers

Session Lifecycle (Serena MCP Memory Integration)

Session Start Protocol (Auto-Executes Every Time)

During Work (Continuous PDCA Cycle)

What this file has done since we first saw it

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