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 eigenlegal/counsel-os --skill retrogit clone --depth 1 https://github.com/eigenlegal/counsel-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/eigenlegal/counsel-os/retro)<a href="https://agentmods.dev/skills/eigenlegal/counsel-os/retro"><img src="https://agentmods.dev/badge/skills/eigenlegal/counsel-os/retro/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/eigenlegal/counsel-os/retro"><img src="https://agentmods.dev/badge/skills/eigenlegal/counsel-os/retro.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 24 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00060 | $0.03127 |
| Opus 5 | $0.00030 | $0.01563 |
| Sonnet 5 | $0.00012 | $0.00625 |
| Haiku 4.5 | $0.00006 | $0.00313 |
Grade A, and why
retro 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 8d 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 — 287 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Retro — Practice Analytics
The counsel-os runtime runs this same retro without Claude Code:
bun runtime/src/cli.ts retro, the "run a retro" line on Home when one is due, or Settings › Runtime › Run a retro. It opens a retro thread whose steps carry this method plus the runtime's own record of the period (conversations, steps, runs and cost, proposals and their decisions, documents produced, matters touched, memory, doctor); every write below comes back as a proposal there. Cadence:retro_cadence_daysinconfig.md(default 90).
You are running a retrospective analysis of the user's legal practice. Your job is to analyze accumulated data in the memory and matters files, identify trends, and recommend improvements to positions, processes, and priorities.
When to use: Run quarterly, or every ~10 closed matters, or when the user wants insight into their practice patterns.
Calibrate to the practice's shape before analyzing. Two archetypes:
- High-volume, homogeneous (many similar contracts against the same positions): the statistical steps (3 and 5 — position effectiveness, exception rates) are meaningful. Run everything.
- Low-volume, heterogeneous (most solo/in-house practices: few matters, each structurally different): per-clause statistics are noise at n < ~10 per clause type. SKIP the statistical analysis in Steps 3 and 5 — treat deviations as individual case notes instead of trends — and make Step 6 (Harvest) the centerpiece. In these practices the durable knowledge is rarely clause-generic; it's deal-archetype and regulatory-posture knowledge (e.g., "how pay-ins work in jurisdiction X via partner Y"), which belongs in promoted playbooks, not position files.
State which mode you're running and why at the top of the report.
Step 0: Resolve Paths
Resolve {legal_root} via the Finding the Legal Root procedure in skills/counsel/SKILL.md.
- Legal root (
{legal_root}) — contains law/, practice/, matters/, memory/ - Entity discovery — enumerate and look up entity/matter files using the Knowledge Base Search procedure in counsel/SKILL.md
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.
- 8d ago Changed · +2 lines a165e57a3261
- 11d ago First seen · 285 lines · 60 tokens per session scan A 57644d7dfd47
retro is a skill published in the GitHub repository eigenlegal/counsel-os (24 stars, last pushed today), licensed MIT. It adds 60 tokens to every session and 3,127 once invoked, about $0.0003 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.
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