AC DeepReader
The default web content reader for OpenClaw. Reads X (Twitter), Reddit, YouTube, and any webpage into clean Markdown — zero API keys required. Use when you need to ingest social media posts, articles, or video transcripts into agent memory.
As a process C 62/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, consistency
IntegrationYouTubeMedia and videoAI and agentsWriting and documentstype and topics are labelled automatically from the skill text
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: 15. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens)
Process rating: all ten parameters 62/100
- 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
- 40Consistency. Frontmatter name (DeepReader) differs from the folder (deepreader-skill)
- 50Failures and branches. 0 branches, has a failure section
- 60Result and completion. Output format stated, no completion criterion
- 100Tools and files. No external tools needed
- 100Steps. 5 steps
- 100Execution cost. Instruction body is 580 tokens
- 100Running it twice. No mutating operations
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)
- +1No license
- +2Single-language instructions
- +3Description length 240: enough signal without eating the budget
- +4Structure: 7 headings
- +3Step-by-step instructions: 5 items
- +3Output format is stated explicitly
- +4Has examples (3 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.
External checks
ClawHub: clean
DeepReader is a coherent web-reading skill that fetches links and saves extracted content to local agent memory, with expected privacy and prompt-injection cautions.
LLM: benign (high) · VirusTotal: benign · 27 May 2026