Borrowing it
Nothing to install: this file belongs to zkysar1/Claude-Mind. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/zkysar1/Claude-Mind/main/.claude/skills/reflect-on-self/SKILL.mdgit clone --depth 1 https://github.com/zkysar1/Claude-MindWrote 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/zkysar1/claude-mind/reflect-on-self)<a href="https://agentmods.dev/skills/zkysar1/claude-mind/reflect-on-self"><img src="https://agentmods.dev/badge/skills/zkysar1/claude-mind/reflect-on-self/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/zkysar1/claude-mind/reflect-on-self"><img src="https://agentmods.dev/badge/skills/zkysar1/claude-mind/reflect-on-self.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00096 | $0.04872 |
| Opus 5 | $0.00048 | $0.02436 |
| Sonnet 5 | $0.00019 | $0.00974 |
| Haiku 4.5 | $0.00010 | $0.00487 |
Grade A, and why
reflect-on-self 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 12d 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 — 416 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/reflect-on-self — Self-Model Reflection
This sub-skill implements self-model reflection modes for /reflect. It is invoked
by the parent router for two modes:
- Patterns mode (
--extract-patterns): Mine resolved hypotheses for strategies, synthesize Level 1 patterns, build Level 2 strategic self-model - Calibration mode (
--calibration-check): Analyze confidence calibration across all hypotheses
Each mode section below is self-contained with its own step numbering.
Mode: Extract Patterns (--extract-patterns)
This sub-skill implements Mode 2 of /reflect. It is invoked by the parent /reflect router when --extract-patterns is specified, or during --full-cycle after individual hypothesis reflections complete. It mines the full resolved population — --stage resolved AND --stage archived, per Step 1 — for reusable strategies, synthesizes Level 1 patterns and Level 2 strategic self-models, and updates the knowledge base.
Step 0: Load Conventions
Step 0: Load Conventions — Bash: load-conventions.sh with each name from the conventions: front matter. Read only the paths returned (files not yet in context). If output is empty, all conventions already loaded — proceed to next step.
Step 1: Load the Full Resolved Population (resolved AND archived)
# BOTH stages are REQUIRED. `--stage resolved` alone is a SURVIVORSHIP FILTER:
# `resolved` is the small live holding area and records migrate to `archived`
# as they age, so most scoreable records sit in `archived`. Measured
# 2026-08-04T03:33 (bravo, hostname cc-05, uname -r 6.8.0-136-generic):
# resolved 86 vs archived 829 — resolved is 9.4% of the 915-record store.
# Pattern MINING is the worst possible consumer of that filter: a "recurring
# pattern" needs 3+ instances (Step 2), and mining 9.4% of the corpus both
# suppresses real patterns below threshold and lets a small recent cluster
# read as one. The `frequency: N` field emitted below, and the "Category
# accuracy clusters" in the pattern list, are computed straight off this
# fetch. (g-115-4866; template at review-hypotheses Mode 3 Step 1, g-115-3594.)
Bash: pipeline-read.sh --stage resolved
Bash: pipeline-read.sh --stage archived
# Mine the UNION of the two. Keep EXPIRED / UNRESOLVABLE out of any rate the
# patterns below assert (store-wide convention: only CONFIRMED and CORRECTED
# are scoreable) — but they remain legitimate inputs to non-rate pattern
# mining, so do not drop the records themselves.
Read all Level 0 reflections from journal entries
Read existing pattern files from $WORLD_DIR/knowledge/patterns/
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.
- 12d ago First seen · 416 lines · 96 tokens per session scan A add2b1491705
reflect-on-self is a skill published in the GitHub repository zkysar1/Claude-Mind (5 stars, last pushed yesterday), licensed MIT. It adds 96 tokens to every session and 4,872 once invoked, about $0.0005 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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obsidian
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