SKILLEMALL.ai

BB Clients

Manages client relationships end to end for freelancers, consultants, and agencies: qualifying leads, scoping, onboarding, scope creep, getting paid. Use when a prospect enquires and the call is whether to take them, when a proposal or SOW has to be scoped and priced, when onboarding needs access, stakeholders and approvals, when the client keeps adding "one small thing", when an invoice is late and the chase has to escalate, when a client goes quiet or the relationship is decaying, when rates have to go up on an existing client, when an engagement is renewing, expanding, or ending, and when a client has to be fired or a hard conversation drafted. Covers retainers versus project work, change orders, procurement, handover, and referrals. Not for drafting the contract itself (`contract`), issuing invoices (`invoice`), filing received invoices (`invoices`), a personal contact book (`people`), running an agency as a business (`agency`), or platform tactics on Upwork (`upwork`).

ClawHub Agent Skills author: Iván v1.0.2 MIT-0 16 files body ≈ 5 885 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process B 79/100 · Nearly there — weak spots: inputs and preconditions

GeneratorFinancetype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
66
Run on models
none yet
Process rating
B
79/100
Nearly there
Inputs and preconditions w 11
0
Result and completion w 14
60
Failures and branches w 10
70
the three weakest of ten parameters · all ten

How to improve

  1. 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: 16. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning body-long SKILL.md body ≈ 5885 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "homepage"
  • note frontmatter-key unknown frontmatter key "changelog"

Process rating: all ten parameters 79/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 60Result and completion. Output format stated, no completion criterion
  • 70Failures and branches. 6 branches
  • 70Execution cost. Instruction body is 5885 tokens
  • 100Tools and files. No external tools needed
  • 100Steps. 39 steps
  • 100When it triggers. States when to use and when not to
  • 100Consistency. Name and required fields are in place
  • 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 12 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (4 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
  • +3Description length 988: 120–800 characters recommended
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 39 items
  • +3Output format is stated explicitly

Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.

External checks

ClawHub: clean
This is a disclosed local client-management skill that keeps client notes, contacts, projects, and commercial history on the user’s machine, with explicit rules not to store credential values.
LLM: benign (high) · VirusTotal: · 27 Jul 2026