SKILLEMALL.ai

BD send-me-my-files-r2-upload-with-short-lived-signed-urls

Upload files to Cloudflare R2, AWS S3, or any S3-compatible storage and generate secure presigned download links with configurable expiration.

sundial-org/awesome-openclaw-skills Agent Skills author: sundial-org 10 files body ≈ 732 tokens Open the sourcegithub.com analyzed 2 d ago

Upload files to Cloudflare R2, AWS S3, or any S3-compatible storage and generate secure presigned download links with configurable expiration.

As a process D 48/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorAWSCloudflareInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
95
Quality 40%
71
Run on models
none yet
Process rating
D
48/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
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 · 5

✓ No critical or high findings

Medium and low: 5
  • low Secrets in code secret-high-entropy-token pnpm-lock.yaml:50
    High-entropy token-like string (may be an id, hash or a credential)
    resolution: {integrity: sha512-+iWb8…YNf+ly5S…Rag==}
  • low Secrets in code secret-high-entropy-token pnpm-lock.yaml:63
    High-entropy token-like string (may be an id, hash or a credential)
    resolution: {integrity: sha5…wIN//F77/IADDSs58i+MDaO…jeo+YFg==}
  • low Secrets in code secret-high-entropy-token pnpm-lock.yaml:121
    High-entropy token-like string (may be an id, hash or a credential)
    resolution: {integrity: sha5…Bnt+aV0eAJ7uc+ouNo…sDq+a0lWFM/XpyRWraqA==}
  • low Secrets in code secret-high-entropy-token pnpm-lock.yaml:129
    High-entropy token-like string (may be an id, hash or a credential)
    resolution: {integrity: sha5…vix+1VAt…AQx/FjhhlpSTwuXd+LRhUEVb3MaA==}
  • low Secrets in code secret-high-entropy-token pnpm-lock.yaml:165
    High-entropy token-like string (may be an id, hash or a credential)
    resolution: {integrity: sha5…6lL+G6JH…aiq+/fhkU…9KA==}

Files scanned: 10. 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")
  • note frontmatter-key unknown frontmatter key "summary"

Process rating: all ten parameters 48/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 5 mutating operations with no state check
  • 85Steps. 24 steps, 1 vague phrases
  • 100Tools and files. No external tools needed
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 732 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 142: enough signal without eating the budget
  • +4Structure: 14 headings
  • +3Step-by-step instructions: 24 items
  • +4Has examples (7 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.