claude-reflect is a self-learning system for Claude Code that records corrections, positive feedback, preferences, and recurring workflows as persistent instructions or reusable skills. It helps Claude Code users retain lessons across sessions and improve repeated tasks, with catalogue add-ons providing its hooks, commands, instructions, plugin, and skill.
Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add BayramAnnakov/claude-reflect/plugin install claude-reflectWrote 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/commands/bayramannakov/claude-reflect/reflect-skills)<a href="https://agentmods.dev/commands/bayramannakov/claude-reflect/reflect-skills"><img src="https://agentmods.dev/badge/commands/bayramannakov/claude-reflect/reflect-skills/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/commands/bayramannakov/claude-reflect/reflect-skills"><img src="https://agentmods.dev/badge/commands/bayramannakov/claude-reflect/reflect-skills.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 | $0.00007 | $0.02677 |
| Opus 5 | $0.00003 | $0.01339 |
| Sonnet 5 | $0.00001 | $0.00535 |
| Haiku 4.5 | $0.00001 | $0.00268 |
Grade A, and why
reflect-skills 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 11d 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 — 363 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Arguments
--days N: Analyze sessions from last N days (default: 14)--project <path>: Analyze sessions from a specific project (default: current project)--all-projects: Analyze ALL projects (slower, use when looking for cross-project patterns)--dry-run: Show analysis without generating skill files
Context
- Current project: !
pwd - Session files location:
~/.claude/projects/ - Skills location:
.claude/commands/(per-project) or~/.claude/commands/(global)
Your Task
You are analyzing session history to discover repeating patterns that could become reusable skills.
IMPORTANT: AI-Powered Detection
DO NOT use hardcoded patterns, regex, or keyword matching.
Your job is to reason about the sessions and identify:
- Workflow patterns - Multi-step sequences the user requests repeatedly
- Misunderstanding patterns - Corrections that keep happening (could become skill guardrails)
- Prompt sequences - Similar intents expressed in different words
Use your semantic understanding. The same intent might appear as:
- "search for X on linkedin"
- "find X's linkedin profile"
- "lookup X on linkedin"
These are the same pattern despite different wording.
Workflow
Step 1: Initialize Task Tracking
REQUIRED: Use TodoWrite immediately to show progress. Update after each step.
{
"todos": [
{"content": "Parse arguments", "status": "in_progress", "activeForm": "Parsing command arguments"},
{"content": "Gather session data", "status": "pending", "activeForm": "Reading session files"},
{"content": "Check existing commands", "status": "pending", "activeForm": "Checking existing commands"},
{"content": "Analyze for patterns", "status": "pending", "activeForm": "Analyzing sessions for patterns"},
{"content": "Propose skill candidates", "status": "pending", "activeForm": "Proposing skill candidates"},
{"content": "Assign skills to projects", "status": "pending", "activeForm": "Assigning skills to projects"},
{"content": "Get user approval", "status": "pending", "activeForm": "Getting user approval"},
{"content": "Generate skill files", "status": "pending", "activeForm": "Generating skill files"},
{"content": "Validate skills", "status": "pending", "activeForm": "Validating generated skills"}
]
}
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.
- 11d ago First seen · 363 lines · 7 tokens per session scan A 3088a46bc74e
reflect-skills is a command published in the GitHub repository BayramAnnakov/claude-reflect (1,430 stars, last pushed 5mo ago), licensed MIT. It adds 7 tokens to every session and 2,677 once invoked, about $0.0000 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 2026-08-30.
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