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Search Slack public channels, read joined conversations, and send user-confirmed bot messages.

AceDataCloud/Skills Agent Skills author: AceDataCloud 1 file body ≈ 1 579 tokens Open the sourcegithub.com↗ analyzed 2 h ago

Search Slack public channels, read joined conversations, and send user-confirmed bot messages.

As a process D 42/100 · Unfinished process — weak spots: steps, result and completion, inputs and preconditions

ReferenceSlackData and analyticsInfrastructuretype 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
70/100
safety, quality, tests
Safety 60%
74
Quality 40%
65
Run on models
none yet
Process rating
D
42/100
Unfinished process
Steps w 15
0
Result and completion w 14
0
Inputs and preconditions w 11
0
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. 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 · 6

✓ No critical or high findings

Medium and low: 6
  • medium Exfiltration exfil-send-secrets-to-url SKILL.md:18
    Instruction to send secrets/history to an external endpoint (describes API authentication (bearer / header / HTTPS); destination is a well-known publishing service; the skill's own vendor host)
    search. Send either token only to `https://slack.com/api/` over HTTPS. Check
    API authknown servicevendor-host
  • medium Exfiltration net-credential-use SKILL.md:60
    Credential used in a network call (verify the destination is the intended service)
    curl -sS -H "Authorization: Bearer $SLACK_TOKEN" \
  • medium Exfiltration net-credential-use SKILL.md:70
    Credential used in a network call (verify the destination is the intended service)
    curl -sS -G -H "Authorization: Bearer $SLACK_TOKEN" \
  • medium Exfiltration net-credential-use SKILL.md:82
    Credential used in a network call (verify the destination is the intended service)
    curl -sS -G -H "Authorization: Bearer $SLACK_TOKEN" \
  • medium Exfiltration net-credential-use SKILL.md:87
    Credential used in a network call (verify the destination is the intended service)
    curl -sS -G -H "Authorization: Bearer $SLACK_TOKEN" \
  • low Exfiltration net-credential-use SKILL.md:16
    Credential used in a network call (verify the destination is the intended service) (detector / deny-list definition)
    bot token in `$SLACK_TOKEN` for joined-channel reads and confirmed sends.
    detector

Files scanned: 1. 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 "connections"
  • note frontmatter-key unknown frontmatter key "allowed_tools"
  • note edit-residue the text marks something as outdated (lines 14): 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

  • 0Steps. Prose only: no discrete steps
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 6 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 100Failures and branches. 3 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1579 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)
  • +3Description length 94: 120–800 characters recommended
  • +3No numbered steps or checklist
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +4Structure: 7 headings
  • +4Has examples (7 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.