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.
Generate tech news digests with unified source model, quality scoring, and multi-format output.
As a process C 61/100 · Has gaps — weak spots: result and completion, when it triggers, running it twice
The same skill appears in 2 more places: ClawHub, 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.
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.
Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.
How to improve
- 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.
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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-secretSKILL.md:1Skill 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 purposerequired_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-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "homepage" - note
frontmatter-keyunknown frontmatter key "source" - note
frontmatter-keyunknown frontmatter key "env" - note
frontmatter-keyunknown frontmatter key "tools" - note
frontmatter-keyunknown frontmatter key "files"
Process rating: all ten parameters 61/100
- 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
- 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
- 100Consistency. Name and required fields are in place
- 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.
In the sandbox The scripts kept to themselves
The skill's scripts were run in a throwaway machine: no network, fake keys in the home directory, a tracer watching. We wrote down what they did. Reaching for the network or for secrets caps the technical grade at C; a quiet run adds no points.
Запущено 12 скриптов, ещё 4 не поместились в лимит; каждому дали двадцать секунд, поддельный домашний каталог с ключами и сеть, в которой ничего нет.
Из них 4 не дошли до работы, и об их поведении мы ничего не узнали.
scripts/config_loader.py | ничего за пределами своей папки |
scripts/enrich-articles.py | не запустился: enrich-articles.py: error: the following arguments are required: --input/-i |
scripts/fetch-github.py | не завершился за отведённое время |
scripts/fetch-reddit.py | не завершился за отведённое время |
scripts/fetch-rss.py | ничего за пределами своей папки |
scripts/fetch-twitter.py | ничего за пределами своей папки |
scripts/fetch-web.py | ничего за пределами своей папки |
scripts/generate-pdf.py | не запустился: generate-pdf.py: error: the following arguments are required: --input/-i, --output/-o |
scripts/merge-sources.py | ничего за пределами своей папки |
scripts/run-pipeline.py | не завершился за отведённое время |
scripts/sanitize-html.py | не запустился: sanitize-html.py: error: the following arguments are required: --input/-i, --output/-o |
scripts/send-email.py | не запустился: send-email.py: error: the following arguments are required: --to, --subject/-s, --html |
26 Sept 2026