BB endpoint-aiops
Use this skill whenever the user needs to operate a managed-endpoint fleet (thin clients, VDI endpoints, centrally-managed devices) — a one-shot fleet health overview, endpoint inventory (list/get), a composite per-endpoint health score (which endpoints are worst?), login & boot sessions, login-storm analysis (detect morning login storms and rank the slowest login/boot contributors), patch/config drift (which endpoints deviate from the fleet baseline), and two guarded writes (assign a config profile, reboot an endpoint). Always use this skill for "endpoint fleet overview", "list managed endpoints", "which endpoints are worst", "endpoint health score", "rank endpoints by risk", "why is login slow this morning", "login storm", "boot time analysis", "patch drift", "config drift", "which endpoints are behind on patches", "assign a profile to an endpoint", or "reboot a thin client" when the context is an endpoint-management fleet. Do NOT use when the target is OT / industrial equipment (Modbus, OPC-UA, PLCs — use industrial-aiops), a hypervisor, a storage appliance, a backup product, a Kubernetes cluster, or a network device (negative routing hints only). Covers common managed-endpoint operations with a built-in governance harness (audit, policy, token budget, undo, risk-tiers). The test suite is mock-based; not yet exercised against a live management server (see docs/VERIFICATION.md).
Use this skill whenever the user needs to operate a managed-endpoint fleet (thin clients, VDI endpoints, centrally-managed devices) — a one-shot fleet health…
As a process B 71/100 · Nearly there — weak spots: result and completion, inputs and preconditions
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.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.
Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.
How to improve
- Shorten the description to 1024 characters.
- 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 · 2
✓ No critical or high findings
Medium and low: 2
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medium Exfiltration
intent-browser-credential-storeskill-card.md:33Accesses a browser credential / cookie store (documentation of a security skill)Risk: Endpoint credentials, the master password, and local state under ~/.endpoint-aiops/ are sensitive operational data.
security skill -
medium Broad scope
meta-broad-allowed-toolsSKILL.md:1Broad tool permissions pre-approved: Bashallowed-tools: Bash
Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
description-longdescription is 1404 chars, limit 1024 - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "summary" - note
frontmatter-keyunknown frontmatter key "homepage" - note
frontmatter-keyunknown frontmatter key "installer"
Process rating: all ten parameters 71/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 55Failures and branches. 1 branches
- 100Tools and files. Tools declared in frontmatter
- 100Steps. 32 steps
- 100When it triggers. States when to use and when not to
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2021 tokens
- 100Running it twice. No mutating operations
- 100Progress reporting. Reports progress
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
- +3Description length 1403: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +5Description quotes 13 example trigger phrases
- +4Description says when NOT to use the skill
- +4Structure: 12 headings
- +3Step-by-step instructions: 32 items
- +4Has examples (1 code blocks)
- +4Reference files are cited in the instructions (3 of 4)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.