BB integrate-backend
Analyzes the user's business problem and recommends the right backend integration approach — Web API, AI Web API (generative summaries / grounded search), Server Logic, Cloud Flows, or a combination — for a Power Pages site, then routes to the appropriate specialized skill. Use when the user wants to add backend integration, connect to data, add AI summaries, or needs help deciding which backend approach to use.
Analyzes the user's business problem and recommends the right backend integration approach — Web API, AI Web API (generative summaries / grounded search)…
As a process B 68/100 · Nearly there — weak spots: result and completion
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 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
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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 · 1
✓ No critical or high findings
Medium and low: 1
-
medium Broad scope
meta-broad-allowed-toolsSKILL.md:1Broad tool permissions pre-approved: Bashallowed-tools: Read Write Edit Bash Grep Glob AskUserQuestion Skill Task TaskCreate TaskUpdate TaskList
Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 7816 tokens (recommended < 5000); move details to references/ - note
edit-residuethe text marks something as outdated (lines 64): check that old rules are not kept next to new ones — the full check reads the text for contradictions
Process rating: all ten parameters 68/100
- 0Result and completion. Does not say what the result is
- 60Steps. 72 steps, 4 vague phrases
- 65Failures and branches. 3 branches
- 70When it triggers. States when to use, but not when not to
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Execution cost. Instruction body is 7816 tokens
- 100Tools and files. Tools declared in frontmatter
- 100Consistency. Name and required fields are in place
- 100Running it twice. Mutating operations check current state
- 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
- +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
- -5TODO / placeholder text left in the skill
- +1No license
- +2Single-language instructions
- +3Description length 415: enough signal without eating the budget
- +4Structure: 25 headings
- +3Step-by-step instructions: 72 items
- +4Has examples (19 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.