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AC agent-reach

只读读取各平台内容：搜索、读帖、看评论、取字幕、查行情和职位。 Use when 用户提到或贴出链接：小红书/xiaohongshu、B站/bilibili、Twitter/X、Reddit、 YouTube（字幕、转录）、GitHub、V2EX、雪球/股票行情、LinkedIn/Boss直聘 职位、 Instagram、Facebook、小宇宙播客；或说"帮我搜/看看/读一下这个链接"而自带网页搜索/读取不可用、失败或拿不到正文； 或要安装、加上/去掉某个平台、登录/退出、看状态、更新、卸载 Agent Reach。 不做：发帖、评论、点赞、私信等任何写操作；不替用户登录、不索要密码。 公开内容优先用 Agent 自带工具，Reach 补缺口。

Panniantong/Agent-Reach Agent Skills author: Panniantong MIT 5 files body ≈ 827 tokens Open the sourcegithub.com↗ analyzed 5 d ago

只读读取各平台内容：搜索、读帖、看评论、取字幕、查行情和职位。 Use when 用户提到或贴出链接：小红书/xiaohongshu、B站/bilibili、Twitter/X、Reddit、 YouTube（字幕、转录）、GitHub、V2EX、雪球/股票行情、LinkedIn/Boss直聘 职位、…

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureGitHubYouTubeAI and agentstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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: 5. 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

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 2 mutating operations with no state check
    • 40Consistency. Frontmatter name (agent-reach) differs from the folder (skill)
    • 50Failures and branches. 0 branches, has a failure section
    • 100Tools and files. No external tools needed
    • 100Steps. 16 steps
    • 100Execution cost. Instruction body is 827 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
    • +1No license
    • +2Single-language instructions
    • +3Description length 327: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 16 items
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.