SKILLEMALL.ai

BC erpclaw

AI-native ERP system. Full accounting, invoicing, inventory, purchasing, tax, billing, HR, payroll, advanced accounting (ASC 606/842, intercompany, consolidation), and financial reporting (including P&L / trial balance / spend grouped by department, project, cost center, location, or fund). 496 actions across 14 domains, 45 optional expansion modules (user-approved install from GitHub). Double-entry GL, immutable audit trail, US GAAP compliant. Licensed under GNU GPL v3 (the marketplace "MIT-0" badge is a ClawHub platform default; the LICENSE.txt in the bundle is GPL v3).

ClawHub Hermes author: Nikhil Jathar v4.15.0 MIT-0 80 files body ≈ 11 710 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process C 55/100 · Has gaps — weak spots: result and completion, inputs and preconditions, execution cost

ProcedureGitHubTelegramFinancetype and topics are labelled automatically from the skill text
JSON
Technical rating
B
83/100
safety, quality, tests
Safety 60%
100
Quality 40%
58
Run on models
none yet
Process rating
C
55/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Execution cost w 6
40
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 · 0

✓ No critical or high findings

Files scanned: 80. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 579 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 ≈ 11710 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "homepage"
  • note frontmatter-key unknown frontmatter key "source"

Process rating: all ten parameters 55/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 40Execution cost. Instruction body is 11710 tokens: crowds the task out of the window
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (bash, web, git, python) that frontmatter does not declare
  • 60Consistency. The Hermes dialect needs category and tags
  • 100Steps. 17 steps
  • 100Failures and branches. 7 branches, has a failure section
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • 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
  • +2Single-language instructions
  • +3Description length 578: enough signal without eating the budget
  • +4Structure: 24 headings
  • +3Step-by-step instructions: 17 items
  • +4Has examples (2 code blocks)
  • +3All 1 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 58.

External checks

ClawHub: suspicious
ERPClaw is a coherent local ERP skill, but it needs Review because it can change financial and payroll records, manage credentials, and install/update executable modules while some controls and disclosures are under-scoped.
LLM: suspicious (high) · 16 Aug 2026