DD screenpipe-api
Query the user's local and synced-device data via the screenpipe REST API at localhost:3030 — recordings, audio, UI, meetings, connected services, and memory. Use for starred work, screen activity, other-device or cross-device history, productivity, media export, connections, durable memory, or discovering and automating saved workflows.
Query the user's local and synced-device data via the screenpipe REST API at localhost:3030 — recordings, audio, UI, meetings, connected services, and memory.
As a process D 42/100 · Unfinished process — References files that are not bundled: url, ~/Documents/q3.md
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".
If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- The text references files that are not there: add them or drop the references.
- 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
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medium Exfiltration
net-credential-useSKILL.md:150Credential used in a network call (verify the destination is the intended service)curl -H "Authorization: Bearer $SCREENPIPE_LOCAL_API_KEY" \
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medium Exfiltration
net-credential-useSKILL.md:240Credential used in a network call (verify the destination is the intended service)curl -H "Authorization: Bearer $SCREENPIPE_LOCAL_API_KEY" \
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medium Exfiltration
net-credential-useSKILL.md:259Credential used in a network call (verify the destination is the intended service)curl -H "Authorization: Bearer $SCREENPIPE_LOCAL_API_KEY" \
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medium Exfiltration
net-credential-useSKILL.md:294Credential used in a network call (verify the destination is the intended service)curl -H "Authorization: Bearer $SCREENPIPE_LOCAL_API_KEY" \
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medium Exfiltration
net-credential-useSKILL.md:316Credential used in a network call (verify the destination is the intended service)curl -H "Authorization: Bearer $SCREENPIPE_LOCAL_API_KEY" \
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 11233 tokens (recommended < 5000); move details to references/ - warning
missing-refreference to a missing file: url - warning
missing-refreference to a missing file: ~/Documents/q3.md - note
edit-residuethe text marks something as outdated (lines 62, 70): check that old rules are not kept next to new ones — the full check reads the text for contradictions
Process rating: all ten parameters 42/100
- 0Tools and files. 2 referenced file(s) missing: url, ~/Documents/q3.md
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 14 mutating operations with no state check
- 40Execution cost. Instruction body is 11233 tokens: crowds the task out of the window
- 50When it triggers. No condition that starts the skill
- 85Steps. 44 steps, 1 vague phrases
- 100Failures and branches. 3 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 24 top-level sections: this looks like several domains in one skill
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
- -4Absolute local paths (C:\Users, /home/…): not portable
- -2localhost URLs: will not work for another user
- +1No license
- +2Single-language instructions
- +3Description length 339: enough signal without eating the budget
- +4Structure: 26 headings
- +3Step-by-step instructions: 44 items
- +4Has examples (23 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 59.