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 qte77/claude-code-plugins --skill mining-session-patternsgit clone --depth 1 https://github.com/qte77/claude-code-pluginsWrote 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/qte77/claude-code-plugins/mining-session-patterns)<a href="https://agentmods.dev/skills/qte77/claude-code-plugins/mining-session-patterns"><img src="https://agentmods.dev/badge/skills/qte77/claude-code-plugins/mining-session-patterns/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/qte77/claude-code-plugins/mining-session-patterns"><img src="https://agentmods.dev/badge/skills/qte77/claude-code-plugins/mining-session-patterns.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 | $0.00037 | $0.00958 |
| Opus 5.5 | $0.00015 | $0.00383 |
| Sonnet 5.5 | $0.00007 | $0.00192 |
| Haiku 4.5 | $0.00004 | $0.00096 |
Grade A, and why
mining-session-patterns 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 17d 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 — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Session Pattern Mining
Target: $ARGUMENTS
Mines Claude Code session transcripts for recurring patterns that feed compound learning. Converts raw session data into actionable improvements.
Arguments
| Position | Name | Required | Default | Description |
|---|---|---|---|---|
| 1 | time-range |
no | 7d |
Period to scan. E.g. 7d, 30d, this-week. |
| 2 | output-path |
no | docs/patterns/session-patterns.md |
Where to write findings. |
Examples:
/mining-session-patterns # Last 7 days, default output
/mining-session-patterns 30d # Last 30 days
/mining-session-patterns 7d ./patterns.md # Custom output path
Data Source
~/.claude/projects/*/*.jsonl # Session transcripts
Critical: Never bulk-read full .jsonl files. Use sampling strategy below
to respect context budget.
Workflow
-
Discover session files — Glob
~/.claude/projects/*/*.jsonl. Filter by mtime withintime-range. Select up to 10 files, preferring recent. -
Sample each file — Read first 20 lines + last 20 lines per file. This captures session setup (tools, config) and final outcomes (errors, completions). Skip files smaller than 5 lines.
-
Extract patterns from sampled lines:
- Error-fix sequences: Tool call with error response followed by a
successful retry or different approach. Look for
type: "tool_error"or error messages in tool results, then the next tool call on the same target. - Tool failure rates: Count tool calls and failures per tool type (Bash, Edit, Read, Grep, Glob, Write). A failure is any tool result containing error indicators.
- Cost signals: Estimate token usage per session from message counts and approximate message sizes. Map to task complexity (small/medium/large) based on message count thresholds: <20 small, 20-80 medium, >80 large.
- Error-fix sequences: Tool call with error response followed by a
successful retry or different approach. Look for
-
Format findings — Structure as tables per Output Format below. Every row must suggest a concrete improvement or be omitted.
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.
- 17d ago Changed 043cc919f392
- 23d ago Changed · +37 tokens per session f4eb5d4e942b
- 1mo ago First seen · 109 lines · 0 tokens per session scan A 374514a6300b
mining-session-patterns is a skill published in the GitHub repository qte77/claude-code-plugins (3 stars, last pushed 4d ago), licensed Apache-2.0. It adds 37 tokens to every session and 958 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-31.
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