AC content-research-and-sourcing
The research-and-sourcing craft — verify the substance of a piece before it publishes: trace stats to primary sources, kill zombie stats, catch AI-hallucinated citations, and attribute properly on social. Use when someone has a stat-heavy draft to make publish-ready, wants to check if a viral statistic is real, asks how to cite sources, used AI research output, or is making health/finance claims. Uses the FACTS framework. Reads brand-profile + the piece's format skill first. AI-supplied citations are guilty until verified; a working link is not verification; aggregators are leads, not the source; where none exists, reframe as owned observation or commission data. The agent verifies where it has search; the human clicks links where it doesn't; verification happens before scheduling; WoopSocial publishes. Never invents studies or reuses retracted stats. Distinct from idea-generation, data-and-original-research, quote-cards, and infographic-and-data-viz.
The research-and-sourcing craft — verify the substance of a piece before it publishes: trace stats to primary sources, kill zombie stats, catch…
As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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: 3. 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 51/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 4 mutating operations with no state check
- 40Result and completion. Does not say what the result is
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 100Steps. 10 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1797 tokens
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low No test case covers injection arriving through data
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)
- +3Description length 965: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +4Structure: 9 headings
- +3Step-by-step instructions: 10 items
- +4Reference files are cited in the instructions (4 of 4)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.