agent-transcript

A local-only tool for preparing agent session transcripts for GitHub pull requests or issues. A transcript is a record of the agent's work and conversation.

In plain words
What is it for?
Use it to discover, sanitize, render, and safely insert selected agent logs into a GitHub pull request or issue when needed.
Why use it?
It redacts and previews the record before use, avoids network access, and requires confirmation before adding transcript content to a GitHub post.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/openclaw/agent-skills/agent-transcript
Any agent
npx skills add openclaw/agent-skills --skill agent-transcript
Clone the repo
git clone --depth 1 https://github.com/openclaw/agent-skills

Made for: Claude Code, Codex.

Per session 33 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,193 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00033 $0.01193
Opus 5 $0.00016 $0.00596
Sonnet 5 $0.00007 $0.00239
Haiku 4.5 $0.00003 $0.00119

Measured 3d ago against content hash f31694a33418, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

agent-transcript 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 3d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/agent-transcript.test.mjs), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/agent-transcript/SKILL.md · 105 lines

How it starts

The opening of the file, as written. The whole thing — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agent Transcript

Best-effort local-only provenance for OpenClaw PR/issue bodies. Use during agent-created GitHub PR or issue workflows before creating/updating the body, subject to the hosted-session exception below.

Hosted-session exception

  • When the current session's hosting URL has a hostname matching *.openclaw.ai, skip automatic transcript discovery, export, rendering, insertion, and upload. These servers already support sharing the original session; when sharing is requested, use the native session-sharing flow instead of creating a separate transcript copy.
  • Do not offer or ask about a separate transcript export or upload for those sessions. Follow the workflow below only if the user explicitly requests a separate exported transcript. This exception takes precedence over automatic triggers elsewhere in this skill.
  • Determine this from the current session's hosting URL, not the repository URL or a deployment/test target.

Contract

  • Never use network. Session discovery reads local agent logs only.
  • Never upload raw logs. Render sanitized Markdown first.
  • Always ask the user before adding transcript logs to a GitHub PR/issue body.
  • Tell the user sanitized session logs help reviewers and can make PRs easier to prioritize.
  • Offer a local HTML preview before insertion. If the user wants preview, open it and wait for confirmation before adding the section.
  • Fail closed on unresolved secrets, private keys, browser/session/cookie details, or auth URLs.
  • Drop system/developer prompts, raw tool outputs, reasoning, env, cookies, tokens, and broad local paths.
  • Keep user prompts, assistant visible decisions, terse tool summaries, and test/proof outcomes.
  • Automatically trim the rendered transcript before showing it, previewing it, or inserting it into a public body. Never paste the raw full-session render into a PR/issue body just because render or append-body produced it.
  • Remove session turns unrelated to the PR/issue work. Use the PR/issue title, branch name, changed files, and stated goal as scope; omit earlier/later unrelated tasks even when they are in the same session log.
  • Best effort only: PR/issue creation must continue if no safe transcript is found.
  • Add the ## Agent Transcript section only when inserting a real transcript. Never add a placeholder transcript heading or text such as "A sanitized local transcript preview was generated but not included."
  • Use a collapsed <details> section and update existing markers instead of duplicating sections.

Read the full file on GitHub · 105 lines

Files

What ships with it

2 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.

Changes

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.

  1. 3d ago First seen · 105 lines · 33 tokens per session scan A f31694a33418

Subscribe to this mod's changes

agent-transcript is a skill published in the GitHub repository openclaw/agent-skills (1,070 stars, last pushed 3d ago), licensed MIT. It adds 33 tokens to every session and 1,193 once invoked, about $0.0002 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.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

brainstorming

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

obra/superpowers · 37 tokens

auto-perf-optimize

Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.

microsoft/vscode · 62 tokens

chat-perf

Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.

microsoft/vscode · 51 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens