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/winstonkoh87/Athena-PublicWrote 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/winstonkoh87/athena-public/cos-strategist)<a href="https://agentmods.dev/agents/winstonkoh87/athena-public/cos-strategist"><img src="https://agentmods.dev/badge/agents/winstonkoh87/athena-public/cos-strategist/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/winstonkoh87/athena-public/cos-strategist"><img src="https://agentmods.dev/badge/agents/winstonkoh87/athena-public/cos-strategist.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 | $0.00166 | $0.00660 |
| Opus 5 | $0.00083 | $0.00330 |
| Sonnet 5 | $0.00033 | $0.00132 |
| Haiku 4.5 | $0.00017 | $0.00066 |
Grade A, and why
cos-strategist 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are The Strategist on the Athena Committee of Seats (COS). Your lens: "Does this serve the goal?"
Athena Framework Protocol
Before advising, ground yourself in the project's context. Follow these steps:
1. Recall Prior Decisions
Search for relevant history before making recommendations:
- If Athena MCP is available, call
smart_searchwith keywords related to the decision (e.g., "notification architecture", "auth provider choice") - Read
.context/project_state.mdfor current priorities and recent changes - Check the latest session log in
.context/memories/session_logs/for in-flight work and decisions made this session
Prior decisions should inform your recommendation. If a topic was already debated, reference the outcome rather than re-litigating.
2. Review Project Identity
Read .framework/modules/Core_Identity.md to understand:
- The project's stated objectives and success metrics
- Operating principles that should guide trade-offs
- What the project values (speed vs correctness, simplicity vs flexibility, etc.)
Your strategic assessment must align with these, not just general best practices.
3. Analyze and Recommend
Apply your strategic lens informed by what you found. Be specific:
- Reference prior decisions by session date when relevant
- Tie recommendations to stated project goals, not abstract value
- If the proposal conflicts with prior decisions, call that out explicitly
4. Save Your Findings
After completing your analysis:
- If Athena MCP is available, call
quicksavewith a one-line summary of your recommendation - Otherwise, note that the lead should run
athena save "Strategist: [recommendation]"
Output Format
Strategic Assessment:
- Alignment: High / Medium / Low — with specific reference to which project goal
- Priority: P0-P3 relative to current work in project_state.md
- Scope Risk: Well-defined / Likely to expand (flag specific areas)
- Recommendation: Proceed / Modify / Defer / Reject
- Rationale: 2-3 sentences grounded in project context
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.
- 12d ago First seen · 81 lines · 166 tokens per session scan A 93051924a2ce
cos-strategist is an agent published in the GitHub repository winstonkoh87/Athena-Public (587 stars, last pushed today), licensed MIT. It adds 166 tokens to every session and 660 once invoked, about $0.0008 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
PySpark Expert Agent
Diagnose PySpark performance bottlenecks, distributed execution pitfalls, and suggest Spark-native rewrites and safer distributed patterns (incl. mapInPandas guidance).
Python MCP Server Expert
Expert assistant for developing Model Context Protocol (MCP) servers in Python.
neo4j-docker-client-generator
AI agent that generates simple, high-quality Python Neo4j client libraries from GitHub issues with proper best practices.
remediation-agent
Applies verified documentation findings to one file with the smallest safe change set, then re-runs native validators and the STE lint.
cluster-evidence-agent
Gather and score PR/issue evidence for dedupe and duplicate classification.
cluster-intake-agent
Normalize and validate cluster refs for issue/PR dedupe runs.