AD account-scoring
Keep every account scored and tiered against your written ICP by a deployed agent that re-scores as accounts arrive and as the ICP changes, writing the rationale back to the CRM. Triggers: "keep our accounts scored as they arrive", "re-score everything when the ICP changes", "which accounts should the team work first", "our scoring is a spreadsheet nobody trusts", "why is this account tier A", "stand up account tiering". Cargo CDK, defineAgent, cargo_score, cargo_tier, HubSpot, Salesforce, Attio. Skip when: someone hands you a list and wants it qualified once, which is cargo-gtm's job, not a deployed scorer's.
Keep every account scored and tiered against your written ICP by a deployed agent that re-scores as accounts arrive and as the ICP changes, writing the…
As a process D 49/100 · 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: 13. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "homepage"
Process rating: all ten parameters 49/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 10 mutating operations with no state check
- 40Result and completion. Does not say what the result is
- 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
- 100Steps. 16 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2624 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +5Description quotes 6 example trigger phrases
- +3Description length 617: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 16 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.