AB x-auto-posting
X (Twitter) auto-posting and content operations workflow: keyword-driven topic collection → case reference extraction → user topic confirmation → tweet drafting → publish to X → 24-hour performance tracking. Executes the complete content cycle from keyword to published tweet in a single run. Use when user mentions post on X, post on Twitter, auto tweet, X auto posting, Twitter auto posting, tweet from keywords, generate tweet, X content operations, X account management, operate X account, schedule tweet, publish tweet, track tweet metrics, X posting workflow, daily X post, X 发推, X 自动发帖, X 运营, 发推文, 推文追踪, 追踪效果, 看数据, 发推, 内容运营.
X (Twitter) auto-posting and content operations workflow: keyword-driven topic collection → case reference extraction → user topic confirmation → tweet…
As a process B 65/100 · Nearly there — weak spots: result and completion, when it triggers, running it twice
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 · 0
✓ No critical or high findings
Files scanned: 17. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 5874 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 65/100
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 37 mutating operations with no state check
- 40Result and completion. Does not say what the result is
- 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Execution cost. Instruction body is 5874 tokens
- 85Steps. 90 steps, 1 vague phrases
- 100Failures and branches. 2 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Progress reporting. Reports progress
- low 17 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (12 tags): a typed call is more reliable
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
- +1No license
- +2Single-language instructions
- +3Description length 631: enough signal without eating the budget
- +4Structure: 33 headings
- +3Step-by-step instructions: 90 items
- +4Has examples (12 code blocks)
- +4Reference files are cited in the instructions (5 of 5)
- +3All 9 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.