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DC screenpipe-api

Query the user's local and synced-device Screenpipe data via the REST API at localhost:3030. Use for screen activity, meetings, apps, productivity, other-device or cross-device history, media export, retranscription, or connected services.

mediar-ai/screenpipe Agent Skills author: mediar-ai NOASSERTION 1 file body ≈ 9 461 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Query the user's local and synced-device Screenpipe data via the REST API at localhost:3030.

As a process C 51/100 · Has gaps — References files that are not bundled: url, ~/Documents/notes/q3.md, ~/Downloads/report.csv

IntegrationAI and agentstype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
D
69/100
safety, quality, tests
Safety 60%
75
Quality 40%
59
Run on models
none yet
Process rating
C
51/100
Has gaps
References files that are not bundled: url, ~/Documents/notes/q3.md, ~/Downloads/report.csv
Tools and files w 18
0
Inputs and preconditions w 11
0
Running it twice w 4
30
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.

Exfiltration 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 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".

For the author

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

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  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 · 5

✓ No critical or high findings

Medium and low: 5
  • medium Exfiltration net-credential-use SKILL.md:15
    Credential used in a network call (verify the destination is the intended service)
    curl -H "Authorization: Bearer $SCREENPIPE_LOCAL_API_KEY" \
  • medium Exfiltration net-credential-use SKILL.md:42
    Credential used in a network call (verify the destination is the intended service)
    curl -H "Authorization: Bearer $SCREENPIPE_LOCAL_API_KEY" \
  • medium Exfiltration net-credential-use SKILL.md:119
    Credential used in a network call (verify the destination is the intended service)
    curl -H "Authorization: Bearer $SCREENPIPE_LOCAL_API_KEY" \
  • medium Exfiltration net-credential-use SKILL.md:160
    Credential used in a network call (verify the destination is the intended service)
    curl -H "Authorization: Bearer $SCREENPIPE_LOCAL_API_KEY" \
  • medium Exfiltration net-credential-use SKILL.md:163
    Credential used in a network call (verify the destination is the intended service)
    curl -H "Authorization: Bearer $SCREENPIPE_LOCAL_API_KEY" \

Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 9461 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: url
  • warning missing-ref reference to a missing file: ~/Documents/notes/q3.md
  • warning missing-ref reference to a missing file: ~/Downloads/report.csv
  • warning missing-ref reference to a missing file: ~/notes/file.md
  • warning missing-ref reference to a missing file: /var/log/app.log

Process rating: all ten parameters 51/100

Will not run. References files that are not bundled: url, ~/Documents/notes/q3.md, ~/Downloads/report.csv
  • 0Tools and files. 5 referenced file(s) missing: url, ~/Documents/notes/q3.md, ~/Downloads/report.csv
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 10 mutating operations with no state check
  • 40Execution cost. Instruction body is 9461 tokens: crowds the task out of the window
  • 50When it triggers. No condition that starts the skill
  • 60Result and completion. Output format stated, no completion criterion
  • 85Steps. 45 steps, 2 vague phrases
  • 100Failures and branches. 1 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 19 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)
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • -2localhost URLs: will not work for another user
  • +1No license
  • +2Single-language instructions
  • +3Description length 239: enough signal without eating the budget
  • +4Structure: 35 headings
  • +3Step-by-step instructions: 45 items
  • +3Output format is stated explicitly
  • +4Has examples (26 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 59.