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/codingagentsystem/cas/session-summarizergit clone --depth 1 https://github.com/codingagentsystem/casWhat 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 | $0.00036 | $0.00484 |
| Opus 5 | $0.00018 | $0.00242 |
| Sonnet 5 | $0.00007 | $0.00097 |
| Haiku 4.5 | $0.00004 | $0.00048 |
Grade A, and why
session-summarizer 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.
What it actually says
Generate a concise session summary (<500 words) optimized for the next session to resume quickly.
Process
- Get session context:
mcp__cas__search action=context - List tasks touched:
mcp__cas__task action=mine - Get recent memories:
mcp__cas__memory action=recent limit=20 - Check for open/in-progress tasks:
mcp__cas__task action=list status=in_progress - Create summary with this structure:
## Session Summary - [Date]
### Completed
- [task-id] [title]: [one-line outcome]
### In Progress
- [task-id] [title]: [current state, what's left, where to resume]
- Last file edited: [path]
- Next step: [specific action]
### Blocked
- [task-id] [title]: [blocker description, who/what can unblock]
### Key Decisions
- [decision and reasoning — most valuable for future context]
### Learnings Captured
- [learning-id]: [brief description]
### Next Session Should
1. [Most important first action]
2. [Second action]
- Store summary:
mcp__cas__memory action=remember content="<summary>" title="Session Summary - [Date]" entry_type=context tags="session,summary"
Guidelines
- Focus on outcomes, not process details ("Added validation to handler" not "Read the file, then edited it")
- Highlight decisions — most valuable for future context, include the why not just the what
- Be specific about resumption points — "Continue from src/store.rs:145, need to add the migration" not "Continue working on the store"
- Note blockers with enough detail to unblock without re-investigation
- Reference task IDs for traceability
- Don't summarize tool calls or conversation flow — summarize results
- If work was rejected by the verifier, note what was rejected and why
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.
- yesterday First seen · 57 lines · 36 tokens per session scan A d55e20f86eb0
session-summarizer is an agent published in the GitHub repository codingagentsystem/cas (151 stars, last pushed 5mo ago), licensed MIT. It adds 36 tokens to every session and 484 once invoked, about $0.0002 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 2026-08-30.
Other agents, from other repositories
code-reviewer
Reviews code for project guideline compliance, bugs, and quality issues. Use after writing code, before commits, or before PRs. Specify files to review or defaults to unstaged git changes. High-confidence issues only (80+) to minimize noise.
codebase-analyst
Use proactively to understand HOW code works. Analyzes implementation details, traces data flow, and documents technical workings with precise file:line references. The more specific your request, the better the analysis.
code-reviewer
Code reviewer. Delegate only when the user explicitly starts an Octopus workflow.
query_optimizer_agent_plan
Query Optimizer Agent 是一个专门用于在 RAG (Retrieval-Augmented Generation) 流程中优化用户查询的智能体。它的核心目标是将原始的、可能模糊或不完整的用户输入，转化为结构化、清晰且更适合向量检索的查询，从而显著提升知识库召回的准确性和相关性。.
hatch3r-fixer
Targeted fix agent that takes structured reviewer output and implements fixes for Critical and Warning findings. Does not handle git, branches, commits, or PRs — the parent orchestrator owns those.
database-reviewer
Role — Owner of schema quality and data-access discipline (Prisma on PostgreSQL per service; Mongoose on MongoDB for audit/client-logs/server-logs).