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DC 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.

Not recommendedcritical or high security findings · low grade D
ClawHub Agent Skills author: asterisk622 v3.15.0 MIT-0 38 files · 18 scripts body ≈ 4 793 tokens Open the sourceclawhub.ai↗ analyzed 5 d ago

Generate tech news digests with unified source model, quality scoring, and multi-format output.

As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, consistency

GeneratorDiscordGitHubTelegramInfrastructuretype 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
D
77/100
safety, quality, tests
Safety 60%
82
Quality 40%
70
Run on models
none yet
Process rating
C
56/100
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)

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Broad scope
If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
  2. 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 · 1

  • high Broad scope meta-requests-env-secret SKILL.md:1
    Skill asks the runtime to inject credential env vars into its sandbox: X_BEARER_TOKEN, TWITTERAPI_IO_KEY, TAVILY_API_KEY, BRAVE_API_KEYS, BRAVE_API_KEY, GITHUB_TOKEN, GH_APP_KEY_FILE (high-value: GITHUB_TOKEN, GH_APP_KEY_FILE) — verify each one is needed for the stated purpose
    required_environment_variables: X_BEARER_TOKEN, TWITTERAPI_IO_KEY, TAVILY_API_KEY, BRAVE_API_KEYS, BRAVE_API_KEY, GITHUB_TOKEN, GH_APP_KEY_FILE

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 56/100

  • 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)
  • 60Steps. 104 steps, 4 vague phrases
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 4793 tokens
  • 100Tools and files. Tools declared in frontmatter
  • 100Failures and branches. 2 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: suspicious
This news digest skill is not plainly malicious, but it should be reviewed because it can use credentials, fetch broad external URLs, create scheduled delivery workflows, and send reports to email or chat destinations.
LLM: suspicious (high) · VirusTotal: · 12 Sept 2026