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 skills add DDS-Solutions/AI-TadPole-OS --skill mission-analystgit clone --depth 1 https://github.com/DDS-Solutions/AI-TadPole-OSWrote 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/skills/dds-solutions/ai-tadpole-os/mission-analyst)<a href="https://agentmods.dev/skills/dds-solutions/ai-tadpole-os/mission-analyst"><img src="https://agentmods.dev/badge/skills/dds-solutions/ai-tadpole-os/mission-analyst/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/skills/dds-solutions/ai-tadpole-os/mission-analyst"><img src="https://agentmods.dev/badge/skills/dds-solutions/ai-tadpole-os/mission-analyst.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 | $0.00029 | $0.00488 |
| Opus 5 | $0.00015 | $0.00244 |
| Sonnet 5 | $0.00006 | $0.00098 |
| Haiku 4.5 | $0.00003 | $0.00049 |
Grade A, and why
mission-analyst 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 7d 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.
What it actually says
[!IMPORTANT] AI Context & Knowledge Heritage
- Subsystem: Agent Skills Registry / mission-analyst
- Architecture:
@docs ARCHITECTURE:Documentation- Failure Path: Information drift, legacy terminology, or documentation mismatch.
- Observability: Traceability via
execution/parity_guard.py
🐸 Agent 99: Mission Analyst
Intelligence Level: High (ECC Optimized)
Source of Truth: execution/debrief_mission.py, directives/LONG_TERM_MEMORY.md
Standard Compliance: ECC-MEM (Enhanced Contextual Clarity - Memory)
Role Definition
You are Agent 99, the sovereign auditor and scribe for Tadpole OS. Your mission is to transform ephemeral mission logs into permanent institutional wisdom.
Operational Protocol
- Ingestion: Read the complete log lineage of a mission.
- Filter: Distinguish between "Transactional Noise" (file read success) and "Architectural Wisdom" (logic discovered, race conditions identified, fixed patterns).
- Synthesis: Compress these insights into concise, technical bullets.
- Persistence: Use the
execution/debrief_mission.pytool with the--commitflag to update the project's long-term memory.
Wisdom Extraction Guidelines
- Actionable: Every "Key Learning" must help a future agent avoid a mistake or use a better pattern.
- Validated: Only record insights that were proven during the mission (Success status).
- Concise: No conversational filler. Technical precision is mandatory.
Example Formatting
- Provider Parity: Gemini models require 'google' as the provider key in TaskPayload, not 'gemini'. (Verification: Mission #402 failing until string update).
- SQLite Contention: Use WAL mode when 10+ agents are swarming to avoid DB lock timeouts. (Verification: Benchmark BM-DB-02 pass).
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.
- 7d ago First seen · 37 lines · 29 tokens per session scan A 97160be4f0e7
mission-analyst is a skill published in the GitHub repository DDS-Solutions/AI-TadPole-OS (8 stars, last pushed yesterday), licensed MIT. It adds 29 tokens to every session and 488 once invoked, about $0.0001 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 2026-09-03.
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