SKILLEMALL.ai

BD agentguard-burn

Find out what used up a Claude Code or Codex usage limit. Runs `npx agentguard-burn why` on this machine's session transcripts, explains where the tokens went, relays the one "Next:" step it prints, and can install the free AgentGuard plugin that holds runaway sub-agent launches. Use when the user hit their Claude Code or Codex limit, asks where their tokens went, why a session cost so much or ran out so fast, or mentions runaway sub-agents.

ClawHub Hermes author: MerchantGuard™ v1.0.0 MIT-0 2 files body ≈ 1 230 tokens Open the sourceclawhub.ai↗ analyzed 7 d ago

Find out what used up a Claude Code or Codex usage limit.

As a process D 46/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches

ProcedureAI and agentsSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
B
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
78
Run on models
none yet
Process rating
D
46/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
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 · 0

✓ No critical or high findings

Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 445 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)

Process rating: all ten parameters 46/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 2 mutating operations with no state check
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 60Consistency. The Hermes dialect needs category and tags
  • 70When it triggers. States when to use, but not when not to
  • 100Steps. 29 steps
  • 100Execution cost. Instruction body is 1230 tokens

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 445: enough signal without eating the budget
  • +4Structure: 7 headings
  • +3Step-by-step instructions: 29 items
  • +4Has examples (3 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.

External checks

ClawHub: suspicious
The skill is mostly coherent, but it directs users to run mutable npm code that reads local Claude Code and Codex transcripts and can optionally install persistent agent-control hooks.
LLM: suspicious (high) · 6 Oct 2026