AD teams-fpx
Read Microsoft Teams data (every chat and channel, their messages, what is unread, inline images, and the Activity feed) from a shell with the fpx CLI (@fetchproxy/cli) instead of running the microsoft-teams-mcp server. A bearer token is captured once from a signed-in teams.cloud.microsoft tab, then Teams' own chat-service REST API is called with plain curl — the Activity feed included, as conversation 48:notifications. Use when you want Teams data without the MCP, in a script, or on a machine where the MCP isn't installed.
Read Microsoft Teams data (every chat and channel, their messages, what is unread, inline images, and the Activity feed) from a shell with the fpx CLI…
As a process D 44/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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 · 0
✓ No critical or high findings
Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 44/100
- 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
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 5 mutating operations with no state check
- 40Consistency. Frontmatter name (teams-fpx) differs from the folder (microsoft-teams-mcp)
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
- 100Steps. 15 steps
- 100Execution cost. Instruction body is 1451 tokens
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low The response is described with custom markup (5 tags): a typed call is more reliable
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 529: enough signal without eating the budget
- +4Structure: 6 headings
- +3Step-by-step instructions: 15 items
- +4Has examples (2 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.