BD Platform Rules Engine
Social media pre-flight checker. Scans any draft post against 30+ platform-specific invisible rules and outputs PASS/WARN/FAIL per rule with exact fix suggestions. Like a linter for content. Covers Reddit (90/10 self-promo ratio, shadowban triggers, link-to-comment tracking), LinkedIn (360Brew AI detection, 60% external link penalty, engagement bait NLP filter, engagement pod detection), Twitter/X (150x author-reply multiplier, 30-min velocity window, link depression since March 2026, bookmark 10x signal), and HackerNews (Show HN format rules, tutorial downrank, clickbait title editing by dang). Research-backed with specific algorithm data. Zero external dependencies.
As a process D 39/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "homepage"
Process rating: all ten parameters 39/100
- 0Result and completion. Does not say what the result is
- 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. 4 mutating operations with no state check
- 40Consistency. Frontmatter name (Platform Rules Engine) differs from the folder (phy-platform-rules-engine)
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 7 steps
- 100Execution cost. Instruction body is 1635 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
- +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
- +2Single-language instructions
- +3Description length 676: enough signal without eating the budget
- +4Structure: 15 headings
- +3Step-by-step instructions: 7 items
- +4Has examples (4 code blocks)
- +3All 1 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 70.