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BC tech-news-digest

Generate tech news digests with unified source model, quality scoring, and multi-format output. Six-source data collection from RSS feeds, Twitter/X KOLs, GitHub releases, GitHub Trending, Reddit, and web search. Pipeline-based scripts with retry mechanisms and deduplication. Supports Discord, email, and markdown templates.

ClawHub Agent Skills author: asterisk622 v3.15.0 MIT-0 38 files · 1 script body ≈ 4 793 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 62/100 · Has gaps — weak spots: result and completion, when it triggers, consistency

GeneratorDiscordGitHubInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw 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) Goose OpenCode
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
70
Run on models
none yet
Process rating
C
62/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: tech-news-digest (ClawHub)

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 30. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "homepage"
  • note frontmatter-key unknown frontmatter key "source"
  • note frontmatter-key unknown frontmatter key "env"
  • note frontmatter-key unknown frontmatter key "tools"
  • note frontmatter-key unknown frontmatter key "files"

Process rating: all ten parameters 62/100

  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 7 mutating operations with no state check
  • 40Consistency. Frontmatter name (tech-news-digest) differs from the folder (dinstein-tech-news-digest)
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 4793 tokens
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 104 steps
  • 100Failures and branches. 4 branches, has a failure section
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 13 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

  • +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
  • -32 of 16 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 325: enough signal without eating the budget
  • +4Structure: 56 headings
  • +3Step-by-step instructions: 104 items
  • +4Has examples (25 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)

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

External checks

ClawHub: clean
This is a coherent tech-news digest skill, but users should configure credentials, delivery targets, enrichment, and archive cleanup deliberately.
LLM: benign (medium) · VirusTotal: · 29 May 2026