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/Jamie-BitFlight/claude_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/commands/jamie-bitflight/claude_skills/explore)<a href="https://agentmods.dev/commands/jamie-bitflight/claude_skills/explore"><img src="https://agentmods.dev/badge/commands/jamie-bitflight/claude_skills/explore.svg" alt="Measured on agentmods" 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 | $0.00014 | $0.00399 |
| Opus 5 | $0.00007 | $0.00199 |
| Sonnet 5 | $0.00003 | $0.00080 |
| Haiku 4.5 | $0.00001 | $0.00040 |
Grade A, and why
explore 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 4d 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
Start an interactive transcript exploration session. Present initial findings from the transcript corpus, then let the user steer deeper investigation.
Arguments
--project <name>— Scope to a specific project transcript directory. Default: current project.
Execution Steps
-
Resolve transcript path. Same logic as
/agentskill-kaizen:analyze— derive project key from--projectflag or current working directory. -
Run initial survey. Use DuckDB MCP to run a quick corpus overview:
- Total session count and date range
- Record type distribution
- Top 10 most-used tools
- Error rate summary
- User interrupt count
-
Present findings to user. Display the survey results and suggest investigation directions:
- "I found {N} sessions with {M} tool misuse violations. Want to dig into those?"
- "I found {K} repeated workflow deviations. Want to compare those sessions?"
- "The most common error is {type} ({count} times). Want to trace those sessions?"
-
Follow user direction. Based on user response, run targeted queries:
- Use DuckDB SQL for structured data extraction
- Use kaizen MCP tools for process mining and pattern detection
- Present results incrementally
- Ask clarifying questions to narrow investigation
-
Save findings on request. When the user wants to save findings, write to
.planning/kaizen/exploration-{date}.md.
Interaction Pattern
This command runs interactively — do NOT spawn an autonomous agent. Stay in the main conversation so the user can steer the investigation in real-time. Use MCP tools directly for queries.
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.
- 4d ago First seen · 41 lines · 14 tokens per session scan A af5d62521bb9
explore is a command published in the GitHub repository Jamie-BitFlight/claude_skills (65 stars, last pushed yesterday), licensed MIT. It adds 14 tokens to every session and 399 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.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.