meta-learn

name	meta-learn
version	3.1.0
description	Deliberate deep-dive capture for a completed skill session that deserves more than the automatic one-line row every T1/T2 skill already logs at its own close — asks three extraction questions (what surprised you, what was wrong, what was missing), turns real answers into specific, falsifiable pattern statements, and logs the session to /context/skill-sessions.md in the same format so meta-synthesis reads one consistent log either way. Trigger on: "capture what we learned", "log this session", "save the learnings", "what did we learn", or any request to encode deeper insights from a completed skill session.
metadata	{"author":"Stefanos Karakasis","context":"context-agnostic","quality_gate":true}
last_updated	2026-08-22T00:00:00.000Z

meta-learn

The deliberate, on-demand deep-dive into a completed skill session — for when the automatic one-line Learning Close every T1/T2 skill already writes isn't enough. Asks what the session actually taught the user — not what the skill's output said, but what surprised them, what they disagreed with, or what was missing. Turns real answers into a specific, falsifiable statement and logs it to the same file, in the same format, every T1/T2 skill's own Learning Close writes to — so meta-synthesis reads one consistent log regardless of which produced any given row.

Trigger

• When: The user wants a deeper capture of a completed skill session than the automatic one-line row every T1/T2 skill already logs at its own close (see that skill's Learning Close step). Use this for a session that deserves real reflection — something surprised the user, a recommendation felt wrong, or important context was missing — and a structured three-question interview is worth the extra few minutes.

• Not for: Auditing a SKILL.md's structure → use meta-review. Checking whether a skill's output itself is correct → use meta-verify. Detecting patterns across multiple sessions or proposing guardrails → use meta-synthesis, which reads what this skill logs.

• Example prompts:

  • "Capture what we learned from that retro"
  • "Log this session"
  • "What surprised you about that positioning run?"
  • "Save the learnings before we close"

Inputs

• Args: The completed session's skill name and a short description of its output. n.v.t. if invoked immediately after a skill session in the same conversation — infer both from context.
• Defaults: If the skill name isn't obvious, ask for it before proceeding.
• Context keys: /context/skill-sessions.md — appended to, created if it doesn't exist yet.

Pre-flight

• This skill is context-agnostic. Do not load /foundation/brain.md and do not let prior company context shape what counts as a pattern — extraction comes from the user's answers alone.
• If there's no completed session to close out (skill hasn't produced output yet), stop and say so — this isn't a mid-session check-in.

Steps

Step 1: Confirm the Session Closed

Confirm which skill just ran and what it produced, in one line:

"Closing out [skill-name] — produced [one-line description of output]. Three quick questions before we log this."

Step 2: Ask the Three Extraction Questions

Ask all three in one message. Wait for complete answers before proceeding.

"1. What surprised you? Something unexpected the skill surfaced that you hadn't considered.

2. What was wrong or off? Any recommendation you pushed back on or felt missed the mark. Be specific: what, and why?

3. What was missing? Context the skill didn't have, a question it didn't ask, an output it should have produced but didn't."

If all three come back as "nothing," skip to Step 5 — log a clean close, no pattern extraction needed.

Step 3: Make Each Answer Falsifiable

For any answer with real content, restate it as a specific, testable statement — not a vague impression.

• ❌ Vague: "communication could be better"
• ✅ Falsifiable: "when the launch timeline slips more than 10 days, the brief didn't flag which stakeholders needed to be renotified"

If an answer can't be sharpened into something falsifiable, it isn't a pattern yet — note it as a loose observation rather than forcing it into a false-precision statement.

Step 4: Show What Will Be Logged

Before writing, show the user the exact log entry:

🔁 SESSION LEARNING

Skill: [name]
Date: [date]
Pattern: [falsifiable statement, or "none — clean session"]
Source: [surprised / wrong / missing]

Log this? (yes / edit / skip)

Never log a pattern without this confirmation. A clean close (no pattern) logs automatically without this gate — there's nothing to approve.

Step 5: Append to the Session Log

Append one row to /context/skill-sessions.md (create the file with a header row if it doesn't exist yet):

skill: [name]
session_date: [YYYY-MM-DD]
pattern: [falsifiable statement, or "none"]
source: [surprised / wrong / missing / n.v.t.]

This is the only file this skill writes to. meta-synthesis is what reads across many of these rows later to find what repeats — this skill's only job is making sure each individual row is worth reading.

Outputs

• Files written: /context/skill-sessions.md — one appended row per session, per Step 5.
• Chat output format: The three questions (Step 2), the falsifiable restatement if applicable (Step 3), and the logged-entry confirmation (Step 4).
• External side effects: n.v.t.

Verification

• The session log entry exists in /context/skill-sessions.md with today's date and the correct skill name.
• If a pattern was captured, it's stated as a specific, falsifiable claim — not a vague impression.
• Nothing was written without the Step 4 confirmation, except a clean close with no pattern.

Do Not Use For

• meta-review — auditing a SKILL.md's own structure against the spec
• meta-verify — checking whether a skill's output itself is correct before it goes out
• meta-synthesis — detecting patterns across 2+ logged sessions and proposing guardrails; this skill only produces the raw log rows meta-synthesis later reads

Operating Rules

• Extract from the user's real answer, not from the skill's own output. The skill already said what it produced. This is about what the user noticed that it didn't say.
• Falsifiable or nothing. A pattern statement that can't be proven wrong isn't useful to meta-synthesis later — sharpen it or log it as a loose observation, don't force false precision.
• Never force a pattern. If the user says "nothing surprised me," accept that and log a clean close. Don't manufacture insight to seem thorough.
• One log, one format. Every session appends to /context/skill-sessions.md in the same YAML shape — meta-synthesis depends on consistent structure to scan across sessions.
• Nothing writes without the confirmation gate, except the automatic clean-close log entry when there's genuinely nothing to approve.
• This skill doesn't decide what's a repeating pattern. That's meta-synthesis's job, reading across many logged sessions. This skill's job ends at logging one session well.

Quality Gate

Check	Standard	Pass =
All three questions asked	Surprised / wrong / missing, in one message	Yes
Pattern is falsifiable	Specific claim, not a vague impression	Yes or n.v.t. (clean close)
Confirmation shown before write	Exact log entry shown, user confirmed	Yes or n.v.t. (clean close)
Log entry appended	/context/skill-sessions.md has the new row	Yes
Clean closes handled	"Nothing" answers don't force a fake pattern	Yes