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 commands/hknc/claude-evolve/signalgit clone --depth 1 https://github.com/hknc/claude-evolveWrote 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/hknc/claude-evolve/signal)<a href="https://agentmods.dev/commands/hknc/claude-evolve/signal"><img src="https://agentmods.dev/badge/commands/hknc/claude-evolve/signal.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 | $0.00039 | $0.00349 |
| Opus 5 | $0.00019 | $0.00175 |
| Sonnet 5 | $0.00008 | $0.00070 |
| Haiku 4.5 | $0.00004 | $0.00035 |
Grade A, and why
signal 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 5d 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.
What it actually says
/evolve signal
Flag that this session has valuable insights worth capturing with /learn.
When to use
- Found root cause of a bug
- User corrected your approach
- Discovered a non-obvious pattern
- Session had reusable insights
Usage
/evolve signal # Flag current insight
/evolve signal "found auth bug" # Flag with description
Implementation
Run this bash command:
# Requires $CLAUDE_SESSION_ID (exported by SessionStart hook)
if [[ -z "$CLAUDE_SESSION_ID" ]]; then
echo "[claude-evolve] Error: Session ID not available. Signal not saved."
exit 1
fi
SIGNAL_DIR="$HOME/.claude-evolve/signals"
mkdir -p "$SIGNAL_DIR"
DESCRIPTION="${1:-insight flagged}"
# Escape quotes for valid JSON
ESCAPED_DESC=$(echo "$DESCRIPTION" | sed 's/"/\\"/g')
# Append as JSONL (one JSON object per line)
echo "{\"summary\":\"$ESCAPED_DESC\",\"ts\":\"$(date -Iseconds)\",\"cwd\":\"$(pwd)\"}" >> "$SIGNAL_DIR/${CLAUDE_SESSION_ID}.json"
echo "[claude-evolve] Insight flagged. Run /learn to capture."
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.
- 5d ago First seen · 52 lines · 39 tokens per session scan A af6ce50f8871
signal is a command published in the GitHub repository hknc/claude-evolve (8 stars, last pushed 7mo ago), licensed MIT. It adds 39 tokens to every session and 349 once invoked, about $0.0002 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.
Other commands, from other repositories
minutes-ideas
Surface recent voice memos and ideas captured from any device. Use when the user asks "what ideas did I have?", "what were my recent memos?", "what did I record while walking?", or wants to recall a captured thought.
learn
Force claude-smart to extract learnings from this session now.
session-end
I'll summarize this coding session and update the memory system with our accomplishments.
memory-store
Store an insight, decision, or pattern to memory.
analyze-context
USE WHEN you want to analyze project context before starting work on a task. Calls context + recall, then synthesizes goals, decisions, gotchas, and relevant memories into a pre-task brief.
cc-memory
Configure persistent memory that survives across sessions using a layered approach: split rule files for always-loaded context, auto-memory for organic learning, and optional MCP-backed long-term memory for large codebases.