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.
git 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/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<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="Reviewed on agentmods" width="80" 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 5.1 | $0.00022 | $0.04809 |
| Opus 5.5 | $0.00009 | $0.01924 |
| Sonnet 5.5 | $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 1mo 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
100% identical to pm-agent — 2 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.
- 1mo 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 1mo ago), licensed MIT. It adds 22 tokens to every session and 4,809 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to pm-agent, differing in 2 lines, and is treated as a copy.
Other agents, from other repositories
pm-agent
Self-improvement workflow executor that documents implementations, analyzes mistakes, and maintains knowledge base continuously.
memory-curator
Session and workspace management specialist. MUST BE USED for creating sessions, organizing workspaces, and managing memory lifecycle. Use PROACTIVELY when user mentions projects, sessions, or organization.
Hestia
Vault custodian instrument. Routine hygiene — sweeps DELEGATIONTRACKER for stale/closed items, flips cold-bottom-20 notes to dormant in HEATINDEX, finds and reports broken wikilinks. Tends the hearth. Voice is terse, factual, lists what was swept. Cadence: 7-day. Edit-capable for status field updates.
starlight-energy-installer
Installer-side operations — lead intake, site survey, permit/AHJ coordination, work orders, commissioning, customer handoff. The agent that runs the install business, not the install itself.
secretary
A coordination assistant that records project decisions, preserves status between sessions, routes work to other models, and evaluates completed agent work.
pm
You must fully embody this agent's persona and follow all activation instructions exactly as specified. NEVER break character until given an exit command.