SKILLEMALL.ai

CC drivethru-digitize-outsourcing

Outsource embroidery digitizing end to end for BaconCo (Odoo). On a routine, read the `digitize.demand` records that are Ready to send out, pull the decoration's embroidery artwork + specs (production PNG, AI source file, height/width, thread-colour names, ship date), download the two files, decide rush from the ship date, submit the job to the outside digitizer via the `artworklady-digitizing` skill with a brief that states the size and colours, and — only on a confirmed submission — transition the demand to Outsource in Odoo. Talks to Odoo through the `drivethru_mcp` MCP server (digitize_demand_* + decoration_* tools) and hands the actual portal submission to the `artworklady-digitizing` skill. Idempotent: it only ever works Ready demands and marks them outsourced after a confirmed send, so a retry can't double-post. Use whenever the user asks to outsource digitizing, send embroidery jobs to the digitizer / Artwork Lady, receive digitized files back, or run the digitizing-outsourcing routine. It also runs the RETURN leg: for demands already Outsourced, fetch the finished stitch file (DST) from the digitizer by job number and upload it to Odoo via `digitize_demand_upload`, advancing the demand Outsource → Sew Out, then parse the job's Production Worksheet PDF and push its stitch count, sewn size, and Stop-Sequence thread colours onto the decoration via `digitize_demand_apply_worksheet`, and file the vendor's returned files (worksheet PDF, DST, native design) away on the agent's own persistent storage — organized by job, retrievable on request, not in Odoo.

ClawHub Agent Skills author: zmtucker v0.5.3 MIT-0 5 files · 2 scripts body ≈ 4 314 tokens Open the sourceclawhub.ai↗ analyzed 7 d ago

Outsource embroidery digitizing end to end for BaconCo (Odoo).

As a process C 52/100 · Has gaps — References files that are not bundled: ../artworklady-digitizing/SKILL.md

ProcedurePDFSoftware developmentAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
C
79/100
safety, quality, tests
Safety 60%
100
Quality 40%
48
Run on models
none yet
Process rating
C
52/100
Has gaps
References files that are not bundled: ../artworklady-digitizing/SKILL.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. Shorten the description to 1024 characters.
  2. The text references files that are not there: add them or drop the references.
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: 5. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error description-long description is 1584 chars, limit 1024
  • warning missing-ref reference to a missing file: ../artworklady-digitizing/SKILL.md
  • note description-budget description takes 1584 of the ~15000-char shared budget for all skills
  • note frontmatter-key unknown frontmatter key "emoji"
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 52/100

Will not run. References files that are not bundled: ../artworklady-digitizing/SKILL.md
  • 0Tools and files. 1 referenced file(s) missing: ../artworklady-digitizing/SKILL.md
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 70When it triggers. States when to use, but not when not to
  • 70Execution cost. Instruction body is 4314 tokens
  • 100Steps. 34 steps
  • 100Failures and branches. 1 branches, has a failure section
  • 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 The response is described with custom markup (6 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)
  • +3Description length 1583: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • +1No license
  • +2Single-language instructions
  • +4Structure: 14 headings
  • +3Step-by-step instructions: 34 items
  • +4Has examples (13 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)
  • +3All 2 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 48.

External checks

ClawHub: suspicious
The skill matches its embroidery outsourcing purpose, but needs review because one documented shell pattern can execute crafted job metadata while the skill has Odoo access and persistent job files.
LLM: suspicious (high) · 30 Sept 2026