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 sugarforever/01coder-agent-skills --skill mining-session-skillsgit clone --depth 1 https://github.com/sugarforever/01coder-agent-skillsWrote 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/sugarforever/01coder-agent-skills/mining-session-skills)<a href="https://agentmods.dev/skills/sugarforever/01coder-agent-skills/mining-session-skills"><img src="https://agentmods.dev/badge/skills/sugarforever/01coder-agent-skills/mining-session-skills/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/sugarforever/01coder-agent-skills/mining-session-skills"><img src="https://agentmods.dev/badge/skills/sugarforever/01coder-agent-skills/mining-session-skills.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 | $0.00113 | $0.01305 |
| Opus 5 | $0.00056 | $0.00652 |
| Sonnet 5 | $0.00023 | $0.00261 |
| Haiku 4.5 | $0.00011 | $0.00130 |
Grade B, and why
mining-session-skills scanned grade B with 1 finding 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 9d 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
Search by the user's description. Prefilter optionally with a raw-JSONL byte grep across `~/.claude/projects` (finds which file mentions a keyword without parsing), and/or grep the exported corpus under `~/.claude/sessio How it starts
The opening of the file, as written. The whole thing — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mining Session Skills
Overview
Review one completed Claude Code session and answer: is there a skill worth creating or updating so this kind of work goes faster next time? A clean "nothing worth making here" is a valid result.
This skill is the judgment layer on top of claude-session-manager (the export/normalization layer). It reads exported markdown, not raw JSONL.
Preconditions
- Inventory = skills loaded in THIS session. Create-vs-update-vs-reuse is decided against the skills already advertised/loaded in the running session. State this limit in the report ("comparison limited to skills loaded this session"). Run this skill where the relevant skills are loaded.
- Mining operates on exported markdown (default
~/.claude/session-markdown), produced byclaude-session-manager. If the target session is not exported yet, export it first (step 1.5).
Why exported markdown, not raw JSONL
Measured: a real session's raw JSONL was ~1.5M tokens (exceeds the context window); the exported compact body was ~91k tokens (17× smaller) with tool payloads deferred to a sidecar. Raw grep '"type":"user"' over JSONL is a trap (tool results are role:user). Always read/mine the exported markdown. Raw-JSONL byte grep is acceptable ONLY as a location prefilter (step 1).
Pipeline
Copy this checklist and track progress:
- [ ] 1. Locate the session (keyword search; confirm with user)
- [ ] 1.5 Export it if not already exported
- [ ] 2. Read the compact transcript (pull sidecar only as needed)
- [ ] 2.5 Segment into topic arcs
- [ ] 3. Mine friction signals per arc
- [ ] 4. Apply the worth-it gate
- [ ] 5. Decide create / update / reuse
- [ ] 6. Present the proposal
- [ ] 7. On approval, interview + draft
1. Locate
Search by the user's description. Prefilter optionally with a raw-JSONL byte grep across ~/.claude/projects (finds which file mentions a keyword without parsing), and/or grep the exported corpus under ~/.claude/session-markdown. Skip <local-command-caveat> / <command-*> wrapper noise — the first-prompt excerpt is often a wrapper, not the real ask. Present a ranked shortlist and let the user confirm.
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 78 lines · 113 tokens per session scan B 7a3bbb3bff51
mining-session-skills is a skill published in the GitHub repository sugarforever/01coder-agent-skills (134 stars, last pushed 2mo ago), licensed MIT. It adds 113 tokens to every session and 1,305 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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