AC postqued-api
Operate Postqued through its remote MCP server or v2 REST API. Use for social content uploads, multi-platform publishing and scheduling, calendar status, analytics, engagement, approval workflows, revisions, caption suggestions, client reviews, collaborators, connected accounts, workspaces, and billing capability checks. Trigger whenever an agent needs to read or change Postqued data, publish to supported social platforms, or integrate Postqued into an automated workflow. For OpenClaw setup and more information, see https://postqued.com/openclaw.
Operate Postqued through its remote MCP server or v2 REST API.
As a process C 62/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
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: 6. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
edit-residuethe text marks something as outdated (lines 29): check that old rules are not kept next to new ones — the full check reads the text for contradictions
Process rating: all ten parameters 62/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 21 mutating operations with no state check
- 40Result and completion. Does not say what the result is
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 43 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1423 tokens
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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 552: enough signal without eating the budget
- +4Structure: 11 headings
- +3Step-by-step instructions: 43 items
- +4Has examples (3 code blocks)
- +4Reference files are cited in the instructions (3 of 3)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.