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.
npx agentmods add skills/pantheon-org/tekhne/session-reflectionnpx skills add pantheon-org/tekhne --skill session-reflectiongit clone --depth 1 https://github.com/pantheon-org/tekhneWrote 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/skills/pantheon-org/tekhne/session-reflection)<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>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 | $0.00170 | $0.02685 |
| Opus 5 | $0.00085 | $0.01342 |
| Sonnet 5 | $0.00034 | $0.00537 |
| Haiku 4.5 | $0.00017 | $0.00268 |
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.
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:
- Confidence audit: What am I least confident about right now?
- 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-fileskill, and optionallyadr-captureif a binding decision emerges - For genuine gaps that aren't being fixed in this session: the
context-fileskill'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
- 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.
- 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).
- 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.
- 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.
- 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.
- 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) viacontext-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. - Conclude only once the investigation loop is resolved. Note clearly if new work was spawned.
- 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.
What ships with it
14 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.
- evals/instructions.json 3.0 KB
- evals/scenario-1/capability.txt 124 B
- evals/scenario-1/criteria.json 1.4 KB
- evals/scenario-1/task.md 1.9 KB
- evals/scenario-2/capability.txt 143 B
- evals/scenario-2/criteria.json 1.1 KB
- evals/scenario-2/task.md 1.8 KB
- evals/scenario-3/capability.txt 140 B
- evals/scenario-3/criteria.json 1.3 KB
- evals/scenario-3/task.md 2.1 KB
- evals/summary.json 127 B
- references/recommended-subagent-models.md 4.6 KB
- references/session-reflection-reference.md 2.6 KB
- references/subagent-spawn-pattern.md 2.9 KB
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.
- 3d ago First seen · 187 lines · 170 tokens per session scan A 0cde381a408a
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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