agentleFS
MicrosoftKnown publishermicrosoft/amplifier-bundle-context-intelligence/skills/transcript/SKILL.md

transcript

Skill5 starsChanged 5 days agoMITView on GitHub

Retrieve the prior user and assistant conversation verbatim from the current Context Intelligence capture, or named sessions. Use when a user asks to replay, quote, review, or act on a transcript.

11 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

5 rules. 0 are common, 2 are distinctive, and 3 are very specific to this project.

  • 0

    Common

    Most of the 7 edited versions we read keep these.

  • 2

    Distinctive

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Use session_transcript; never read events.jsonl directly.

    line 12
  2. Distinctive:

    Do not stop after loading the skill, present a proposed tool call, or ask "shall I retrieve it?" The user's request already authorizes this …

    line 16
  3. Very specific:

    No arguments: call session_transcript with no session_ids.

    line 32
  4. Very specific:

    Intent only: call session_transcript with no session_ids, page through the whole transcript, then perform the requested intent using it as …

    line 35
  5. Distinctive:

    If natural language explicitly names a session, pass that ID or prefix to the tool as well.

    line 52

“Common” is measured: kept by at least 6 in 10 of the 7 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Transcript

Use session_transcript; never read events.jsonl directly.

Invoking this skill is a request to retrieve the transcript, not to explain how to retrieve it. Call session_transcript in this turn using the arguments below. Do not stop after loading the skill, present a proposed tool call, or ask "shall I retrieve it?" The user's request already authorizes this read. Only ask for ID clarification after the tool reports ambiguity; honor any actual tool permission gate or explicit user restriction.

Sensitive content: stored captures are replayed verbatim and can contain sensitive content. The logging hook's JSON sanitization is not redaction.

Interpret $ARGUMENTS as follows:

  • ID or ID -- <intent>: a bare full session ID or a hex ID prefix of at least 8 characters (for example, /transcript abcdef12) selects that session. Pass it unchanged in session_ids; the tool resolves it. Do not ask for the full ID first or treat it as an instruction about the current session. With no intent, replay verbatim; with intent, retrieve first, then perform that intent.
  • No arguments: call session_transcript with no session_ids. Return the complete role-marked transcript pages verbatim. Do not summarize or add commentary.
  • Intent only: call session_transcript with no session_ids, page through the whole transcript, then perform the requested intent using it as source material. State that the answer was based on the native transcript.
  • --session ID[,ID...]: retrieve those sessions in the listed order. With no further intent, replay each transcript verbatim under its own session heading.
  • --session ID[,ID...] -- <intent>: retrieve all named sessions first, then perform the intent using those transcripts.

A bare token selects a session only when it actually looks like a capture ID: eight or more hex characters (abcdef12, a full UUID), or the zero-padded sub-agent form 0000000000000000-<hex>[_<agent>]. Anything else is intent about the current session, even when it contains a hyphen, underscore, or digit — chapter-2 and summarize-day-3 are intents, not IDs. When a token could be read either way, treat it as intent: a wrong intent is visible and recoverable, a wrong lookup just fails. For an opaque ID that does not match those shapes, use explicit --session, which accepts unique prefixes and exact opaque IDs. If natural language explicitly names a session, pass that ID or prefix to the tool as well.

On an ambiguous prefix, show the tool's candidates and pass on the length it reports as needed — it names the character position where the candidates diverge, so relay that rather than asking vaguely for "a longer prefix". On a missing session, report that failure. Never choose a candidate, retry against the current session, or delegate to an agent to guess an ID.

A session whose capture directory exists but has no readable metadata.json is reported as capture_unavailable, and an ID whose only captures are derived <id>_<agent> sub-agent sessions is reported as session_not_found listing those sub-agents. Neither is a prompt to substitute one of them; report what the tool said.

For a single session, keep calling session_transcript with its returned full session_id and next_after_event_line as the next after_event_line while has_more is true. For multiple sessions, retrieve and page one session at a time. For a batched follow-up, replace the original prefixes in session_ids with returned full IDs and use those same full IDs as after_event_lines keys. A page boundary is normal; preserve the tool's [MORE MESSAGES AVAILABLE ...] marker between pages. Do not hide capture issues, infer missing messages, use graph reconstruction, or fall back to raw provider events.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.