SKILLEMALL.ai

BD conclave

Conclave is a multi-agent reasoning skill that orchestrates multiple AI CLIs into structured debates. Each agent independently analyzes the problem, challenges competing arguments, identifies flaws and contradictions, and refines the reasoning through multiple rounds of discussion — helping you reach more reliable conclusions than relying on a single AI.

ClawHub Hermes author: MCLYang v1.6.7 MIT-0 11 files · 4 scripts body ≈ 9 777 tokens Open the sourceclawhub.ai analyzed 3 d ago

Conclave is a multi-agent reasoning skill that orchestrates multiple AI CLIs into structured debates.

As a process D 49/100 · Unfinished process — weak spots: result and completion, consistency, execution cost

ProcedureLearningAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
99
Quality 40%
63
Run on models
none yet
Process rating
D
49/100
Unfinished process
Result and completion w 14
0
Consistency w 8
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
  3. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 1

✓ No critical or high findings

Medium and low: 1
  • low Dangerous commands cmd-autorun-instruction scripts/init_debate.sh:107
    Instructs the agent to auto-run a script on every session (string literal in code, not executed)
    echo "       (on a new machine or after CLI failures, first run scripts/install.sh)"
    code literal

Files scanned: 11. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 356 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • warning description-no-when neither description nor a "## When to Use" section says when to use the skill
  • warning body-long SKILL.md body ≈ 9777 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 49/100

  • 0Result and completion. Does not say what the result is
  • 0Consistency. Frontmatter name (conclave) differs from the folder (conclave-skill)
  • 30Running it twice. 29 mutating operations with no state check
  • 40Execution cost. Instruction body is 9777 tokens: crowds the task out of the window
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (bash, web, python, node) that frontmatter does not declare
  • 60Steps. 160 steps, 4 vague phrases
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Failures and branches. 7 branches, has a failure section
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 23 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (9 tags): a typed call is more reliable

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 356: enough signal without eating the budget
  • +4Structure: 43 headings
  • +3Step-by-step instructions: 160 items
  • +4Has examples (2 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)
  • +3All 4 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.

External checks

ClawHub: suspicious
The skill is mostly transparent about its behavior, but it grants broad environment-changing authority and mandatory data retention/export that users should review carefully before installing.
LLM: suspicious (high) · 16 Aug 2026