ai-counsel: Skill for Claude Code

.claude/skills/convergence-debugger/SKILL.md

convergence-debugger is a skill for Claude Code from blueman82/ai-counsel. It costs 43 tokens per session (3,891 once invoked), scanned A, original, MIT.

A debugging guide for a system that decides when several AI responses have reached agreement and can stop discussing a decision.

In plain words
What is it for?
Use it to inspect deliberation transcripts, similarity scores, convergence status, voting results, and the code that detects consensus.
Why use it?
It helps explain wasted discussion rounds, failed early stopping, incorrect similarity measurements, and conflicts between votes and response similarity.

Skill for Claude Code

Written for Claude Code: installed under .claude/. Also seen: mentions Codex.

This is blueman82/ai-counsel's own configuration. It tells Claude Code how to work on ai-counsel itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything ai-counsel configures →

Not installable: its command points at a path on the author’s own machine, so it runs nowhere else. The line is /Users/harrison/Github/ai-counsel/config.yaml.

Reuse

Borrowing it

Nothing to install: this file belongs to blueman82/ai-counsel. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/blueman82/ai-counsel/main/.claude/skills/convergence-debugger/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/blueman82/ai-counsel

Made for: Claude Code.

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Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,891 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00043 $0.03891
Opus 5.5 $0.00017 $0.01556
Sonnet 5.5 $0.00009 $0.00778
Haiku 4.5 $0.00004 $0.00389

Measured 2mo ago against content hash 75cd4a62a52c, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

convergence-debugger 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 2mo 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.

.claude/skills/convergence-debugger/SKILL.md · 480 lines

How it starts

The opening of the file, as written. The whole thing — 480 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Convergence Detection Debugger

Overview

The AI Counsel convergence detection system (deliberation/convergence.py) determines when models have reached consensus and can stop deliberating early. It uses semantic similarity comparison between consecutive rounds, with voting outcomes taking precedence when available.

Common Issue: Convergence not detected → wasted API calls Common Issue: Early stopping not triggering → deliberation runs full max_rounds Common Issue: Semantic vs voting status conflict → confusing results

Diagnostic Workflow

Step 1: Examine the Transcript

What to look for:

  • Are responses actually similar between rounds?
  • Is there a "Convergence Information" section?
  • What's the reported status and similarity scores?
  • Are there votes? What's the voting outcome?

File location:

# Transcripts are in project root
ls -lt transcripts/*.md | head -5

# Open most recent
open "transcripts/$(ls -t transcripts/*.md | head -1)"

Convergence section example:

## Convergence Information
- **Status**: refining (40.00% - 85.00% similarity)
- **Average Similarity**: 72.31%
- **Minimum Similarity**: 68.45%

Voting section example (overrides semantic status):

## Final Voting Results
- **Winner**: TypeScript ✓
- **Status**: majority_decision
- **Tally**: TypeScript: 2, JavaScript: 1

Missing convergence section? → Check if round_number <= min_rounds_before_check (see Step 2)

Step 2: Check Configuration

Read the config:

cat config.yaml

Key settings to verify:

deliberation:
  convergence_detection:
    enabled: true  # Must be true
    semantic_similarity_threshold: 0.85  # Convergence if ALL participants >= this
    divergence_threshold: 0.40  # Diverging if ANY participant < this
    min_rounds_before_check: 1  # Must be <= (total_rounds - 1)
    consecutive_stable_rounds: 2  # Require this many stable rounds

  early_stopping:
    enabled: true  # Must be true for model-controlled stopping
    threshold: 0.66  # Fraction of models that must want to stop (2/3)
    respect_min_rounds: true  # Won't stop before defaults.rounds

Read the full file on GitHub · 480 lines

Changes

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.

  1. 2mo ago First seen · 480 lines · 43 tokens per session scan A 75cd4a62a52c

Subscribe to this mod's changes

convergence-debugger is a skill published in the GitHub repository blueman82/ai-counsel (1 stars, last pushed 27d ago), licensed MIT. It adds 43 tokens to every session and 3,891 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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