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AD merge-travel-pdfs

Automatically merge reimbursement folders into one PDF. Supports recursive folder scanning, PDF merging, two invoices per A4 page, phone screenshots/images placed as A4 half-page slots, and Excel workbooks with multiple sheets converted to PDF before merging.

ClawHub Agent Skills author: harven-droid v1.0.2 MIT-0 4 files body ≈ 1 342 tokens Open the sourceclawhub.ai↗ analyzed 31 h ago

Automatically merge reimbursement folders into one PDF.

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureExcelFinanceData and analyticstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
75
Run on models
none yet
Process rating
D
46/100
Unfinished process
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
20
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.
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: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 46/100

  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 4 mutating operations with no state check
  • 40Consistency. Frontmatter name (merge-travel-pdfs) differs from the folder (merge-reimbursement-pdfs)
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 60Failures and branches. 2 branches
  • 85Steps. 46 steps, 1 vague phrases
  • 100Execution cost. Instruction body is 1342 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 259: enough signal without eating the budget
  • +4Structure: 8 headings
  • +3Step-by-step instructions: 46 items
  • +4Has examples (4 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.

External checks

ClawHub: suspicious
The skill mostly matches its PDF-merging purpose, but it can automatically install Python packages and LibreOffice through system package managers unless disabled.
LLM: suspicious (high) · VirusTotal: · 28 May 2026