session-reflection

session-reflection is a skill for Claude Code, Codex from pantheon-org/tekhne. It costs 170 tokens per session (2,685 once invoked), scanned A, original, MIT.

A session-ending review that asks what the agent is least confident about and what important detail it may have missed. It is a check for blind spots before work is considered finished.

In plain words
What is it for?
Use it when a session is wrapping up, especially after complex work, to identify uncertain results, overlooked risks, or questions that need further research.
Why use it?
It can reveal weak assumptions or missing investigation while there is still time to address them.

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/pantheon-org/tekhne/session-reflection
Any agent
npx skills add pantheon-org/tekhne --skill session-reflection
Clone the repo
git clone --depth 1 https://github.com/pantheon-org/tekhne

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for session-reflection

README.md
[![agentmods](https://agentmods.dev/badge/skills/pantheon-org/tekhne/session-reflection.svg)](https://agentmods.dev/skills/pantheon-org/tekhne/session-reflection)
Your own site
<a href="https://agentmods.dev/skills/pantheon-org/tekhne/session-reflection"><img src="https://agentmods.dev/badge/skills/pantheon-org/tekhne/session-reflection.svg" alt="Measured on agentmods" height="20"></a>
Per session 170 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,685 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 $0.00170 $0.02685
Opus 5 $0.00085 $0.01342
Sonnet 5 $0.00034 $0.00537
Haiku 4.5 $0.00017 $0.00268

Measured 3d ago against content hash 0cde381a408a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

session-reflection 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.

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/agentic-harness/session-reflection/SKILL.md · 187 lines

How it starts

The opening of the file, as written. The whole thing — 187 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Session-End Reflection

Catch blind spots and under-investigated areas before concluding a session by asking two questions:

  1. Confidence audit: What am I least confident about right now?
  2. Blind-spot check (Sam Altman): What's the biggest thing I'm missing about this situation? What don't I realize?

~1 in 4 sessions, one of the answers reveals a critical gap that would silently invalidate work. This skill catches those gaps at the cheapest possible moment: before the user has walked away.

Prerequisites

  • A session that appears to be concluding (user signals completion, asks for summary, or starts wrap-up language)
  • A project-level behavioural rule for "always conduct session-end reflection" should already be active, if this project has one -- check the project's own rules file
  • For persisting uncovered findings: the context-file skill, and optionally adr-capture if a binding decision emerges
  • For genuine gaps that aren't being fixed in this session: the context-file skill's known-issue document type -- this is the primary, intended source of those entries; see Workflow step 6

When to Use

  • A session appears to be concluding: the user signals completion, asks for a summary, or starts wrap-up language.
  • All identified tasks are marked complete and the agent is about to hand back to the user.

When NOT to Use

  • During a brief query that is clearly complete (e.g., "what's the capital of France?") -- the reflection overhead is not justified.
  • When the user has explicitly said "don't do the reflection this time" or similar -- honour it, don't insist.
  • In automated/CI contexts -- this is a human-interactive skill only.
  • In the middle of active work -- only at session-end boundaries.

Workflow

  1. Detect session-end signals: "we're done", "thanks", "that's all", a request for a summary or next steps, or all identified tasks marked complete.
  2. Choose the reflection mode -- inline (default, for short sessions) or sub-agent spawn (preferred for deep sessions with significant work; see Sub-Agent Spawn Pattern).
  3. Initiate the reflection with a natural opening, e.g. "Before we wrap up, I'd like to do a quick reflection." Ask the two questions sequentially, never both at once -- wait for the user's response to each.
  4. Question 1, confidence audit: "What am I least confident about right now?" Generate 3-7 specific items, each naming what was done, what was not verified, and why confidence is low -- not a vague feeling.
  5. Question 2, blind-spot check: "What's the biggest thing I'm missing about this situation?" Target assumptions the user stated but that went unverified, alternatives not explored, and signals dropped mid-conversation.
  6. Follow up. If the user flags an item, investigate before concluding. If a finding warrants preservation, use context-file. If an item is a verified, concrete gap that is NOT being fixed in this session, create a known-issue document (status: ACTIVE, severity: CRITICAL | HIGH | MEDIUM | LOW) via context-file -- this is the primary source of those entries; a reflection item that only lives in chat scrollback is the failure mode this step exists to prevent. Skip this only when the item is being fixed right now instead.
  7. Conclude only once the investigation loop is resolved. Note clearly if new work was spawned.
  8. Verify outcome: confirm with the user that the reflection addressed their concerns, summarize any investigation performed, confirm any known-issue file was actually created, and explicitly ask whether anything else from the reflection needs addressing.

Read the full file on GitHub · 187 lines

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 · 187 lines · 170 tokens per session scan A 0cde381a408a

Subscribe to this mod's changes

session-reflection is a skill published in the GitHub repository pantheon-org/tekhne (10 stars, last pushed 8d ago), licensed MIT. It adds 170 tokens to every session and 2,685 once invoked, about $0.0009 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 2026-08-31.

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