SKILLEMALL.ai

BC nex-deliverables

Client deliverable tracking and project management system for web agencies, design studios, marketing firms, and freelancers managing multiple simultaneous projects and client relationships. Track diverse project deliverables (websites, landing pages, logos, branding guidelines, copywriting, design assets, email campaigns, SEO optimization work, maintenance tasks, testing, documentation) through their complete lifecycle with flexible status tracking (planned, in progress, review, delivered, approved, rejected) and automatic timestamp recording. Monitor deadlines with visual urgency indicators and automatically highlight overdue items for immediate attention. Manage workload across all active clients with built-in statistics on overall delivery rates, average time-to-delivery, overdue percentages, and workload distribution. Generate professional, customizable client status update emails automatically, summarizing what's currently open, what's been recently delivered, and what's overdue to maintain transparency. Search deliverables by title, client name, deliverable type, or priority level with full-text search capabilities. Set priorities (urgent, high, normal, low) and focus on high-priority work. Support for custom deliverable types beyond presets. Perfect for Belgian agency operators who need to stay meticulously organized, communicate transparently with clients about progress, and track project commitments systematically. All deliverable data remains secure and private on your machine.

ClawHub Agent Skills author: Nex AI v1.0.0 MIT-0 9 files · 1 script body ≈ 2 096 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 62/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, running it twice

AnalyzerMarketingWriting and documentsOperations and projectstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
80/100
safety, quality, tests
Safety 60%
95
Quality 40%
57
Run on models
none yet
Process rating
C
62/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

  1. Shorten the description to 1024 characters.
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
  • medium Dangerous commands cmd-shell-rc setup.sh:84
    Writes to a shell startup file
    echo "  Add this to your ~/.bashrc or ~/.zshrc"

Files scanned: 9. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error description-long description is 1513 chars, limit 1024
  • note description-budget description takes 1513 of the ~15000-char shared budget for all skills

Process rating: all ten parameters 62/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 3 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 100Steps. 30 steps
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2096 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)
  • +3Description length 1513: 120–800 characters recommended
  • +2Single-language instructions
  • +4Structure: 22 headings
  • +3Step-by-step instructions: 30 items
  • +3Output format is stated explicitly
  • +4Has examples (13 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 57.

External checks

ClawHub: clean
This is a local client-deliverables tracker with disclosed local storage and no evidence of hidden network access or destructive behavior.
LLM: benign (high) · VirusTotal: · 29 May 2026