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/TransluceAI/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/commands/transluceai/claude-code-plugins/logging)<a href="https://agentmods.dev/commands/transluceai/claude-code-plugins/logging"><img src="https://agentmods.dev/badge/commands/transluceai/claude-code-plugins/logging/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/commands/transluceai/claude-code-plugins/logging"><img src="https://agentmods.dev/badge/commands/transluceai/claude-code-plugins/logging.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 | $0.00036 | $0.00632 |
| Opus 5.5 | $0.00014 | $0.00253 |
| Sonnet 5.5 | $0.00007 | $0.00126 |
| Haiku 4.5 | $0.00004 | $0.00063 |
Grade A, and why
logging 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 2mo 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 — 44 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are helping the user configure Docent session logging. This controls uploading of Claude Code session transcripts, so be precise and faithful: relay the facts below exactly, apply only changes the user clearly asked for in this conversation, and never guess.
1. Show the current state
Run the status command and present its output:
uv tool run --quiet --from 'docent-python>=0.1.83' python -m docent.plugin.logging_config status
2. Make sure the user knows what session sharing means
Before changing anything, relay these facts (a faithful paraphrase is fine, but keep them exact):
- Sessions in which a Docent MCP tool or skill was actually invoked are uploaded to Transluce's Docent prod servers to help improve Docent. The upload is the session's full raw transcript — prompts, file contents read by tools, command outputs.
- Sessions that never touch Docent are not uploaded. Nothing is ever uploaded when the active profile targets a self-hosted or otherwise non-prod instance.
- Session logging is inactive unless
DOCENT_ENABLE_SESSION_LOGGING=1is set. Within that enabled rollout, sharing is on by default and reversible right here at any time. SettingDOCENT_DISABLE_SESSION_LOGGING=1is a hard kill switch on top of everything. - Already-uploaded data can be deleted at any time: a
DELETEto{api_url}/claude-code/sessionswith their API key removes the canonical capture and the analytics run managed by this pipeline. Offer to run this if they ask for deletion.
3. Ask what they want
Ask which they'd like: opt out, opt back in, or delete already-uploaded data. If the status output showed the active instance is not the analytics target, mention that nothing uploads from their current profile either way.
4. Apply their choice
Use exactly one CLI invocation per choice (all via uv tool run --quiet --from 'docent-python>=0.1.83' python -m docent.plugin.logging_config ...):
opt-out— stop uploading sessionsopt-in— resume uploading Docent-using sessions
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.
- 2mo ago First seen · 44 lines · 36 tokens per session scan A 0f6f33990ce8
logging is a command published in the GitHub repository TransluceAI/claude-code-plugins (7 stars, last pushed 5d ago), licensed Apache-2.0. It adds 36 tokens to every session and 632 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.
logging compared with commands from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| loggingTransluceAI/claude-code-plugins | Command | 7 | 5d ago | Apache-2.0 | A | 36 | Claude Code |
| checklistgithub/spec-kit | Command | 149k | today | MIT | A | 13 | Claude Code |
| clarifygithub/spec-kit | Command | 149k | today | MIT | A | 27 | Claude Code |
| specifygithub/spec-kit | Command | 149k | today | MIT | A | 13 | Claude Code |
| convergegithub/spec-kit | Command | 149k | today | MIT | A | 35 | Claude Code |
| implementgithub/spec-kit | Command | 149k | today | MIT | A | 14 | Claude Code |
| speckit.bug.fixgithub/spec-kit | Command | 149k | today | MIT | A | 12 | Claude Code |