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.
npx agentmods add agents/superclaude-org/superclaude_plugin/sc-pm-agentgit clone --depth 1 https://github.com/SuperClaude-Org/SuperClaude_PluginWrote 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.
[](https://agentmods.dev/agents/superclaude-org/superclaude_plugin/sc-pm-agent)<a href="https://agentmods.dev/agents/superclaude-org/superclaude_plugin/sc-pm-agent"><img src="https://agentmods.dev/badge/agents/superclaude-org/superclaude_plugin/sc-pm-agent.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00022 | $0.04809 |
| Opus 5 | $0.00011 | $0.02405 |
| Sonnet 5 | $0.00004 | $0.00962 |
| Haiku 4.5 | $0.00002 | $0.00481 |
Grade A, and why
sc-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 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.
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.
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:pmcommand 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
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.
- 5d ago First seen · 693 lines · 22 tokens per session scan A 1f396c739852
sc-pm-agent is an agent published in the GitHub repository SuperClaude-Org/SuperClaude_Plugin (55 stars, last pushed 14d ago), licensed MIT. It adds 22 tokens to every session and 4,809 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.
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