BC agent-social-reader
Empower your AI agent to read and summarize specific public web or social media links from TikTok, Instagram, X (Twitter), YouTube, Facebook, Reddit, LinkedIn, Threads, Pinterest, Bluesky, Twitch, Snapchat, Kick, Lemon8, Douyin, Xiaohongshu, Weibo, Bilibili, Kuaishou, Xigua, Zhihu, WeChat Official Accounts, WeChat Channels, general public web pages, and RSS feeds. The skill can save a specific retrieved item to Notion, Obsidian, or ima only when the current user request explicitly asks to save/archive it or confirms that exact destination. Trigger when: (1) the user asks to read, summarize, analyze, or extract content from a specific public URL, (2) the user asks what a specific linked video/post/article says, (3) the user asks to subscribe to or inspect a specific RSS feed, or (4) the user asks to save the current retrieved item to Notion, Obsidian, or ima. Triggers: "read this link", "summarize this URL", "what does this video say", "extract this post", "save this to Notion", "save this to Obsidian", "save this to ima".
Empower your AI agent to read and summarize specific public web or social media links from TikTok, Instagram, X (Twitter), YouTube, Facebook, Reddit…
As a process C 60/100 · Has gaps — weak spots: result and completion, inputs and preconditions
How to improve
- Shorten the description to 1024 characters.
- 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 · 1
✓ No critical or high findings
Medium and low: 1
-
low Secrets in code
secret-high-entropy-tokenreferences/tool-details.md:346High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)boundary = "----…0gW"
quoted
Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
description-longdescription is 1039 chars, limit 1024
Process rating: all ten parameters 60/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 70Execution cost. Instruction body is 4970 tokens
- 85Steps. 26 steps, 2 vague phrases
- 100Failures and branches. 6 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 11 top-level sections: this looks like several domains in one skill
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)
- +3Description length 1038: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -214 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +5Description quotes 7 example trigger phrases
- +4Structure: 26 headings
- +3Step-by-step instructions: 26 items
- +4Has examples (12 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.