AB x-algorithm-optimizer
Optimize posts for X's (Twitter's) For You feed algorithm, based on X's open-sourced ranking code. Use when the user wants to write, draft, review, or improve a post/tweet/thread for reach, engagement, or virality on X, for example "write a tweet about...", "make this post go viral", "why isn't my post getting reach", "optimize my thread for the algorithm", "review my tweet before I post". Grounds advice in the actual scoring weights, filters, and distribution mechanics rather than generic social-media tips.
Optimize posts for X's (Twitter's) For You feed algorithm, based on X's open-sourced ranking code.
As a process B 68/100 · Nearly there — weak spots: inputs and preconditions, running it twice, progress reporting
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: 12. 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 68/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 5 mutating operations with no state check
- 55Failures and branches. 1 branches
- 60Result and completion. Output format stated, no completion criterion
- 70When it triggers. States when to use, but not when not to
- 85Steps. 30 steps, 1 vague phrases
- 100Tools and files. No external tools needed
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2115 tokens
- low The skill ranks results itself: that belongs to the system behind the tool, not the model
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)
- +2Single-language instructions
- +5Description quotes 5 example trigger phrases
- +3Description length 513: enough signal without eating the budget
- +4Structure: 12 headings
- +3Step-by-step instructions: 30 items
- +3Output format is stated explicitly
- +4Has examples (1 code blocks)
- +4Reference files are cited in the instructions (6 of 6)
- +3All 1 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 100.