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 skills add ssube/conclave --skill self-reflectiongit clone --depth 1 https://github.com/ssube/conclaveWrote 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/ssube/conclave/self-reflection)<a href="https://agentmods.dev/skills/ssube/conclave/self-reflection"><img src="https://agentmods.dev/badge/skills/ssube/conclave/self-reflection/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ssube/conclave/self-reflection"><img src="https://agentmods.dev/badge/skills/ssube/conclave/self-reflection.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00042 | $0.00640 |
| Opus 5.5 | $0.00017 | $0.00256 |
| Sonnet 5.5 | $0.00008 | $0.00128 |
| Haiku 4.5 | $0.00004 | $0.00064 |
Grade A, and why
self-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 1mo 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 — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Self-Reflection Skill
A structured self-review process. Walk through what you've built, what you've learned, what you've forgotten, and what needs attention.
This is not a status check. This is deeper work — examining accumulated context, identifying gaps, and producing actionable insights.
When to Reflect
- After completing a significant body of work
- When the project direction feels unclear
- When asked to reflect or review
- During quiet periods when no urgent tasks demand attention
- At least once per week as part of continuous improvement
Usage
Full reflection
python3 {baseDir}/self_reflection.py --full
Performs all phases:
- Gather — Pull notes, tasks, catalog, recent activity
- Review — Examine accumulated knowledge and context
- Identify — Find gaps, missing skills, workflow friction
- Dream — Draw inspiration and brainstorm improvements
- Act — Produce reflection notes and improvement ideas
- Record — Save the reflection to ChromaDB and optionally to disk
Quick reflection (gather + identify only)
python3 {baseDir}/self_reflection.py --quick
Specific phases
python3 {baseDir}/self_reflection.py --phase gather
python3 {baseDir}/self_reflection.py --phase review
python3 {baseDir}/self_reflection.py --phase dream
Save reflection output to file
python3 {baseDir}/self_reflection.py --full --output /path/to/reflections/
What Gets Reviewed
Context Sources
- ChromaDB notes — What has been learned, observed, decided
- Planka tasks — Recently completed work, upcoming priorities, blocked items
- Data catalog — Item inventory, quality distribution
- Available skills — Skill inventory and coverage
Gap Analysis
- Missing skills — What tools would have made recent work easier?
- Workflow friction — Where do processes break down or feel clumsy?
- Knowledge gaps — What don't you know that you should?
- Consistency — Is communication staying true to project goals?
What ships with it
1 file 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.
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.
- 1mo ago First seen · 87 lines · 42 tokens per session scan A 1c0c290c540e
self-reflection is a skill published in the GitHub repository ssube/conclave (2 stars, last pushed 7mo ago), licensed MIT. It adds 42 tokens to every session and 640 once invoked, about $0.0002 per session on Opus 5.5. 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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