Mesh API
mr-tbot/mesh-api
Interact with a Meshtastic LoRa mesh network through MESH-API — list nodes, read messages, send texts, and check connection status.
The user asks a question about a video that was already watched or indexed — "what did they say about X", "what error code appears", "what happens at 2:30", "does the video show Y".
Install Asking With Evidence
$ npx skills add oxbshw/watch-skill --skill asking-with-evidence -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install oxbshw/watch-skill asking-with-evidence --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/oxbshw/watch-skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/asking-with-evidence .claude/skills/asking-with-evidence && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "asking-with-evidence" agent skill from https://github.com/oxbshw/watch-skill/tree/main/skills/asking-with-evidence into .claude/skills/asking-with-evidence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "asking-with-evidence", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/oxbshw/watch-skill/tree/main/skills/asking-with-evidenceType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add oxbshw/watch-skill --skill asking-with-evidence -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install oxbshw/watch-skill asking-with-evidence --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/oxbshw/watch-skill.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/asking-with-evidence .agents/skills/asking-with-evidence && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "asking-with-evidence" agent skill from https://github.com/oxbshw/watch-skill/tree/main/skills/asking-with-evidence into .agents/skills/asking-with-evidence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "asking-with-evidence", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add oxbshw/watch-skill --skill asking-with-evidence -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install oxbshw/watch-skill asking-with-evidence --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/oxbshw/watch-skill.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/asking-with-evidence .cursor/skills/asking-with-evidence && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "asking-with-evidence" agent skill from https://github.com/oxbshw/watch-skill/tree/main/skills/asking-with-evidence into .cursor/skills/asking-with-evidence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "asking-with-evidence", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/oxbshw/watch-skill.git --path skills/asking-with-evidence--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add oxbshw/watch-skill --skill asking-with-evidence -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install oxbshw/watch-skill asking-with-evidence --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/oxbshw/watch-skill.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/asking-with-evidence .gemini/skills/asking-with-evidence && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "asking-with-evidence" agent skill from https://github.com/oxbshw/watch-skill/tree/main/skills/asking-with-evidence into .gemini/skills/asking-with-evidence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "asking-with-evidence", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install oxbshw/watch-skill asking-with-evidenceInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add oxbshw/watch-skill --skill asking-with-evidence -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/oxbshw/watch-skill.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/asking-with-evidence .github/skills/asking-with-evidence && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "asking-with-evidence" agent skill from https://github.com/oxbshw/watch-skill/tree/main/skills/asking-with-evidence into .github/skills/asking-with-evidence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "asking-with-evidence", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add oxbshw/watch-skill --skill asking-with-evidence -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install oxbshw/watch-skill asking-with-evidence --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/oxbshw/watch-skill.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/asking-with-evidence .opencode/skills/asking-with-evidence && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "asking-with-evidence" agent skill from https://github.com/oxbshw/watch-skill/tree/main/skills/asking-with-evidence into .opencode/skills/asking-with-evidence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "asking-with-evidence", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
asking-with-evidence- GitHub stars
- 470
- Token cost
- ~550 tokens
- SKILL.md length
- 250 words
- Files
- 1
- Skills in repo
- 10
- Repo updated
- First seen
- Licence
- MIT
At a glance
The user asks a question about a video that was already watched or indexed — "what did they say about X", "what error code appears", "what happens at 2:30", "does the video show Y".
- AI & LLM Engineering work in your project
- SKILL.md covers Answer a question, "What happens at 2:30?", Don't know which video? Search… and When the user corrects you
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Asking With Evidence is an agent skill from oxbshw/watch-skill. The user asks a question about a video that was already watched or indexed — "what did they say about X", "what error code appears", "what happens at 2:30", "does the video show Y". Use this to answer from the persistent index with timestamped evidence and a confidence score instead of re-watching or guessing.
Its SKILL.md is about 550 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in AI & LLM Engineering. It works with Model Context Protocol and DeepSeek. The repository describes itself as: Give AI agents eyes, ears, and verifiable results. Watch Skill turns video, audio and screen activity into searchable, timestamped evidence and proves work with deterministic… The licence is MIT.
When your agent uses it
- AI & LLM Engineering work in your project
Example prompts
- “what did they say about X”
- “what error code appears”
- “what happens at 2:30”
- “/asking-with-evidence”
Requirements
- Pre-approved tools (allowed-tools): Bash, Read
What it can do on your machine
Read from SKILL.md and the folder at commit f1317c8. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
BashRead
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are bash).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Asking With Evidence loads about 550 tokens when it runs. Until then it costs about 83 tokens; SKILL.md has 250 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check: notes
The automated check noted patterns worth knowing about, such as sudo or a known installer.
- NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
allowed-tools: Bash, Read
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from oxbshw/watch-skill at commit f1317c8, republished under its MIT licence (© oxbshw). 250 words, ~550 tokens.
Download SKILL.mdSave it as
.claude/skills/asking-with-evidence/SKILL.md (or your agent's skills folder).- name
- asking-with-evidence
- description
- The user asks a question about a video that was already watched or indexed — "what did they say about X", "what error code appears", "what happens at 2:30", "does the video show Y". Use this to answer from the persistent index with timestamped evidence and a confidence score instead of re-watching or guessing.
- allowed-tools
- Bash, Read
- version
- 1.4.3
- license
- MIT
- user-invocable
- true
Asking with evidence
Every watched video sits in a persistent index. Questions about it are answered from that index — text first, frames only when needed — with timestamps, a confidence score, and an honest refusal when the video does not show the answer. Never re-run a watch for a follow-up.
Answer a question
watch-skill ask <video_id-or-original-url> "<question>"Any language works; the answer comes back in the language of the
question. The engine escalates on its own when unsure (dense re-sampling,
zoom-crop re-OCR, stronger model) and prints a ~N tokens saved line.
Three rules for reading the result:
- Cite the timestamps it gives you; they are real evidence, not decoration.
- Trust the refusal. When it says the video does not clearly show the answer, that is the answer. Do not invent one past it.
- Frame paths are listed only when the engine wants you to look
yourself — Read them then (or force with
--frames).
"What happens at 2:30?"
Moment questions get a dense window, not a whole-video ask:
watch-skill ask <video_id> "what is on screen around 2:30?"The answer engine pulls frames, transcript and OCR around the moment it
resolves. Agents on MCP have a dedicated get_moment tool that takes an
explicit timestamp and window; the CLI answers the same question through
ask.
Don't know which video? Search them all
watch-skill search "<phrase>"Hybrid keyword + semantic search across every video ever watched, with
per-script normalization (Arabic folding, CJK segmentation, Thai
segmentation). Follow a hit with ask or moment on that video.
When the user corrects you
Report it so the next answer is better — see the
learning-from-mistakes skill.
© oxbshw, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/asking-with-evidence of oxbshw/watch-skill.
Open the folder on GitHubat commit f1317c8
Compare with similar skills
Asking With Evidence next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Asking With Evidence this skilloxbshw/watch-skill | 470 | — | ~550 | Automated safety check: Notes | MIT | |
| Mesh APImr-tbot/mesh-api | 180 | — | ~1.8k | Automated safety check: Pass | GPL-3.0 | |
| Dsh PlaybookZSeven-W/dsh-crew | 158 | — | ~1.1k | Automated safety check: Pass | MIT | |
| Auto Review Loop LLMAI4Scientist/nano-scientist | 128 | 3 repos | ~1.8k | Automated safety check: Warn | None | |
| Deepseek Automationzhu1090093659/deepseek-pp | 1.9k | — | ~2.1k | Automated safety check: Notes | Apache-2.0 | |
| Spec Driven Developzhu1090093659/deepseek-pp | 1.9k | — | ~6.9k | Automated safety check: Pass | Apache-2.0 |
Similar skills
Dsh Playbook
ZSeven-W/dsh-crew
How to dispatch well — choosing flash vs pro, writing self-contained briefs, parallelism, verifying results, and guardrails
Auto Review Loop LLM
AI4Scientist/nano-scientist
Autonomous research review loop using any OpenAI-compatible LLM API.
Deepseek Automation
zhu1090093659/deepseek-pp
A skill your agent uses when implementing, resuming, reviewing, or verifying the DeepSeek++ Codex-style automation feature in this repository.
Spec Driven Develop
zhu1090093659/deepseek-pp
Automates pre-development workflow for large-scale complex tasks.
Misakanet Failure Memory
Ikalus1988/MisakaNet
Search and record failure-recovery lessons from real engineering sessions; submit and verify debugging lessons across the MisakaNet network.
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Related
Works with
Categories
Questions about Asking With Evidence
What does Asking With Evidence do?
The user asks a question about a video that was already watched or indexed — "what did they say about X", "what error code appears", "what happens at 2:30", "does the video show Y". Asking With Evidence is an agent skill from oxbshw/watch-skill. The user asks a question about a video that was already watched or indexed — "what did they say about X", "what error code appears", "what happens at 2:30", "does the video show Y".
When should I use Asking With Evidence?
Asking With Evidence fits situations like: AI & LLM Engineering work in your project.
How do I install Asking With Evidence in Claude Code?
Run `npx skills add oxbshw/watch-skill --skill asking-with-evidence -a claude-code`. Or copy the skill folder (skills/asking-with-evidence in oxbshw/watch-skill) into .claude/skills/asking-with-evidence in your project. Claude Code loads it when a task matches its description.
How do I install Asking With Evidence in Codex?
Run `npx skills add oxbshw/watch-skill --skill asking-with-evidence -a codex`. Or copy the skill folder (skills/asking-with-evidence in oxbshw/watch-skill) into .agents/skills/asking-with-evidence in your project. Codex loads it when a task matches its description.
Can I use Asking With Evidence in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add oxbshw/watch-skill --skill asking-with-evidence -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/asking-with-evidence, .gemini/skills/asking-with-evidence, .github/skills/asking-with-evidence and .opencode/skills/asking-with-evidence in your project.
What does Asking With Evidence need to run?
SKILL.md names no scripts, command-line tools or credentials: Asking With Evidence is instructions for the agent only. Its frontmatter pre-approves these tools: Bash, Read.
Does Asking With Evidence access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Asking With Evidence safe to install?
Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
What licence does Asking With Evidence use?
Asking With Evidence is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Asking With Evidence use?
About 550 tokens (SKILL.md is roughly 2.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Asking With Evidence?
Skills that share tags, products or a category with Asking With Evidence: Mesh API (mr-tbot/mesh-api, 180 stars), Dsh Playbook (ZSeven-W/dsh-crew, 158 stars), Auto Review Loop LLM (AI4Scientist/nano-scientist, 128 stars) and Deepseek Automation (zhu1090093659/deepseek-pp, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Asking With Evidence?
oxbshw (a GitHub user) maintains it in oxbshw/watch-skill, which has 470 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on September 14, 2026.
Source: oxbshw/watch-skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.