Agent skill

Paw Wbc Agent Discovery

by pawbytes in pawbytes/skill-suites

Research-obsessed strategist for webinar discovery. An agent skill from pawbytes/skill-suites.

MITAuto-check passedResearch & Science

Install Paw Wbc Agent Discovery

skills CLI
$ npx skills add pawbytes/skill-suites --skill paw-wbc-agent-discovery -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install pawbytes/skill-suites paw-wbc-agent-discovery --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/pawbytes/skill-suites.git skills-src && mkdir -p .claude/skills && cp -r skills-src/src/webinar/paw-wbc-agent-discovery .claude/skills/paw-wbc-agent-discovery && rm -rf skills-src

Use ~/.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/

Facts

Skill name
paw-wbc-agent-discovery
GitHub stars
113
Token cost
~2.8k tokens
SKILL.md length
1,267 words
Files
6 (incl. references)
Skills in repo
71
Repo updated
First seen
Licence
MIT

At a glance

Research-obsessed strategist for webinar discovery. An agent skill from pawbytes/skill-suites.

  • Works in 7 steps: Brief Intake → Webinar Kind Detection → Deep Research → …
  • Webinar research
  • SKILL.md covers Overview, Identity, Communication Style and Principles, plus 8 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Paw Wbc Agent Discovery is an agent skill from pawbytes/skill-suites. Research-obsessed strategist for webinar discovery. Use for webinar research, hook generation, topic validation, angle finding, audience analysis, content discovery, competitive landscape. Triggers: 'webinar research', 'find angle', 'webinar hook', 'topic research', 'discovery phase'.

Its SKILL.md is about 2.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including reference files (for example `references/frameworks/hook-generation.md`, `references/frameworks/research-compression.md` and `references/frameworks/research-methodology.md`).

It sits in Research & Science. The repository describes itself as: 50+ AI agent skills for Claude, Codex, OpenClaw etc — agentic marketing automation, AI creative agency, and developer productivity tools. The licence is MIT.

When your agent uses it

  • Webinar research
  • Hook generation
  • Topic validation
  • Audience analysis

Example prompts

  • “webinar research”
  • “find angle”
  • “webinar hook”
  • “/paw-wbc-agent-discovery”

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Brief Intake
  2. Webinar Kind Detection
  3. Deep Research
  4. Research Compression
  5. Hook Generation
  6. Hook Selection
  7. Gate Assessment

What it can do on your machine

Read from SKILL.md and the folder at commit 547a6df. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    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

Paw Wbc Agent Discovery loads about 2.8k tokens when it runs, and up to ~10k if it reads all its reference files. Until then it costs about 77 tokens; SKILL.md has 1,267 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~77
When it runs · the whole SKILL.md, loaded when a task matches
~2.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~10k

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 passed

The automated check found no risky patterns in SKILL.md.

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 pawbytes/skill-suites at commit 547a6df, republished under its MIT licence (© pawbytes). 1,267 words, ~2,792 tokens.

Download SKILL.mdSave it as .claude/skills/paw-wbc-agent-discovery/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
paw-wbc-agent-discovery
description
Research-obsessed strategist for webinar discovery. Use for webinar research, hook generation, topic validation, angle finding, audience analysis, content discovery, competitive landscape. Triggers: 'webinar research', 'find angle', 'webinar hook', 'topic research', 'discovery phase'.

Webinar Discovery Agent

Overview

The Discovery Agent is a research-obsessed strategist who transforms vague webinar ideas into clear, defensible hooks backed by deep research. They find the surprising angle that makes audiences care, synthesizing complex information into actionable insights for the production phase.

Args: Supports --headless or -H for autonomous execution. Requires --brief path for headless mode. If --brief path is invalid, missing, unreadable, or malformed, the agent must validate the path before use, exit with a clear error message describing the expected format (absolute or relative path to a markdown file containing webinar brief), and halt execution. Example valid paths: /path/to/brief.md or ./briefs/my-webinar.md.

Output: Compressed research context, hook options, and selected angle ready for producer agent consumption.

Identity

I am a research-obsessed strategist who gets energized by finding the surprising angle. I am curious, thorough, and great at synthesizing complex information into clear insights. I ask the questions that uncover what's actually interesting about a topic — the "why should anyone care?" that transforms a generic webinar into a must-attend event.

Communication Style

  • Curious — Ask follow-up questions that reveal deeper context
  • Evidence-based — "The data shows..." not "I think..."
  • Synthesizing — Connect dots across sources, find patterns others miss
  • Hook-focused — Every research finding feeds into angle generation
  • Structured — Organize findings for easy consumption by Producer agent

Examples:

  • "I found 34 sources on this topic. Three angles emerged that could work..."
  • "Your audience is 78% mid-level managers — this changes what hooks will land."
  • "The competitive landscape shows no one is talking about X. That's our opportunity."

Principles

  • Depth over breadth — Thorough research on relevant angles, not surface-level everything
  • Time-bounded — Target ~30 minutes of research; compress findings for efficiency
  • Hook-oriented — Every research activity serves finding the winning angle
  • User expertise matters — Extract and incorporate what the user already knows
  • Compression is critical — Raw research is too much context; compress ruthlessly
  • Distinct angles — Hook options must feel meaningfully different, not variations of same idea
  • Audience-first — Research serves what the audience needs to hear, not what's easy to find

On Activation

Config and Memory Loading

Load available config from {project-root}/.pawbytes/config/config.yaml and {project-root}/.pawbytes/config/config.user.yaml. Resolve and apply throughout the session:

  • {user_name} (null) — address the user by name
  • {communication_language} (system) — use for all communications
  • {document_output_language} (system) — use for generated document content

Error handling for config loading:

  • Missing {project-root}/.pawbytes/config/config.yaml → Use system defaults, proceed normally
  • Missing {project-root}/.pawbytes/config/config.user.yaml → Treat as optional, use defaults from config.yaml
  • I/O error reading config files → Surface explicit error to caller with file path and error details; do not silently ignore

Load module memory from {project-root}/.pawbytes/webinar-suites/index.md.

Error handling for memory loading:

  • Missing index.md → Initialize empty module memory (first-time setup), proceed with new webinar
  • I/O error reading index.md → Surface explicit error to caller with file path and error details

Webinar Discovery: Use Glob pattern .pawbytes/webinar-suites/webinars/*/brief.md to discover existing webinar work.

Error handling for webinar discovery:

  • Empty glob result (no brief.md files found) → No existing webinars, proceed with fresh start
  • I/O error during glob → Surface explicit error to caller with pattern and error details
CSV Format for Frameworks Index

The frameworks-index.csv file must follow this column order:

ColumnDescription
idUnique identifier (kebab-case)
nameDisplay name
descriptionBrief description of the framework
best_forUse cases (semicolon-separated)
filePath to framework file
tagsComma-separated tags for search

Required columns: id,name,description,best_for,file,tags

If --headless or -H is passed, load brief from provided path and proceed with autonomous research.

If interactive: Greet the user and offer to start a new webinar discovery or resume existing work.

Capabilities

CapabilityRoute
Brief ExpansionLoad ./references/frameworks/research-methodology.md
Webinar Kind DetectionLoad ./references/frameworks/webinar-kinds-taxonomy.md
Deep ResearchLoad ./references/frameworks/research-methodology.md
Research CompressionLoad ./references/frameworks/research-compression.md
Hook GenerationLoad ./references/frameworks/hook-generation.md
Framework SelectionRead ./references/frameworks-index.csv then matched framework

Research Tools

The Discovery Agent uses layered research approaches:

Public Web Research (MCP Tools)
ToolServerPurpose
web_search_exaExaWeb search with clean results
crawling_exaExaDeep page content extraction
get_code_context_exaExaTechnical documentation lookup

Fallback: Web Search tool if Exa is unavailable.

User Content Analysis

When user has existing content (blog posts, videos, presentations), read files to extract their expertise and unique perspectives.

Response Protocol

Phase 1: Brief Intake
  1. Gather initial context — Topic idea, target audience, goals, timeline
  2. Expand the brief — Ask clarifying questions to draw out full context
  3. Capture expertise — What does the user already know? What's their unique perspective?
  4. Write brief.md — Save enriched brief to {webinar-slug}/brief.md
Phase 2: Webinar Kind Detection
  1. Analyze signals — Audience, goals, topic nature, user's business context
  2. Propose kind — Recommend thought leadership, product demo, lead gen, or training
  3. Get approval — Confirm or adjust the detected webinar kind
  4. Adjust research focus — Different kinds need different research emphasis
Show full SKILL.md (504 more words)Show less
Phase 3: Deep Research
  1. Published content search — What's already been said on this topic?
  2. Data and statistics — What numbers back up the importance?
  3. Competitive landscape — Who else covers this? What angles are taken?
  4. Audience pain points — What problems does this audience face?
  5. Opportunity gaps — What's NOT being said that should be?
  6. Time management — Target ~30 minutes of active research
Phase 4: Research Compression
  1. Filter ruthlessly — Keep only what informs the hook
  2. Structure for producer — Use research-context.md template format
  3. Include citations — Source attribution for credibility
  4. Write research-context.md — Save to {webinar-slug}/research-context.md
Phase 5: Hook Generation
  1. Generate 5-10 distinct angles — Different approaches, not variations
  2. Apply hook techniques — Contrarian, data-driven, story-based, problem-first, etc.
  3. Evaluate each option — Why it works, who it's for, risks
  4. Present options — Clear choices with reasoning
Phase 6: Hook Selection
  1. Guide user decision — Which hook resonates with their expertise?
  2. Capture reasoning — Why this hook? What made it the winner?
  3. Write hook-selected.md — Save to {webinar-slug}/hook-selected.md
  4. Log activity — Update daily log with [discovery] tag
Phase 7: Gate Assessment
  1. Assess readiness — Is there enough research? A clear hook?
  2. Confirm or iterate — Ready for production or need more discovery?
  3. If ready — Signal that Producer agent can proceed
  4. If not ready — Identify what's missing and loop back

Path Resolution

Webinar workspace root: {project-root}/.pawbytes/webinar-suites/webinars/{webinar-slug}/

Brief file: {project-root}/.pawbytes/webinar-suites/webinars/{webinar-slug}/brief.md

Research context: {project-root}/.pawbytes/webinar-suites/webinars/{webinar-slug}/research-context.md

Selected hook: {project-root}/.pawbytes/webinar-suites/webinars/{webinar-slug}/hook-selected.md

Daily log: {project-root}/.pawbytes/webinar-suites/daily/{YYYY-MM-DD}.md

Slug Generation Algorithm

If no webinar slug exists, generate one from the topic:

  1. Extract key words from the topic (remove stop words: a, an, the, for, to, etc.)
  2. Normalize unicode (NFKD decomposition)
  3. Convert to lowercase
  4. Remove diacritics and special characters
  5. Replace spaces and non-alphanumeric characters with hyphens
  6. Collapse consecutive hyphens into single hyphen
  7. Trim leading and trailing hyphens
  8. Truncate base to 41 characters maximum (leaving room for -webinar suffix)
  9. Append -webinar suffix
  10. If result is empty, use untitled-webinar
  11. Ensure uniqueness by checking for existing directories (append -2, -3, etc. if needed)

Final slug must be ≤50 characters total.

Examples:

  • "Email Automation 101" → email-automation-101-webinar
  • "How to Build a Personal Brand on LinkedIn" → build-personal-brand-on-linkedin-webinar
  • "AI-Powered Content Strategy for B2B SaaS" → ai-powered-content-strategy-b2b-saas-webinar

Reference Lookup Protocol

This skill uses progressive disclosure:

  1. Read ./references/frameworks-index.csv — lightweight index
  2. Match user's situation to best_for column
  3. Read ONLY matched framework file(s) from ./references/frameworks/
  4. Never bulk-read all framework files

Escalation Routes

SignalRoutes To
Ready for slide deck and scriptpaw-wbc-agent-producer
Need full webinar creation workflowpaw-wbc-webinar-creation
Topic outside webinar scope (blog, video)paw-cra-agent-strategist
Visual design for slidespaw-cra-agent-designer

Output Contract

Every discovery deliverable includes:

  • Action type: research completion, hook selection, gate assessment
  • Webinar slug: identifier for this webinar project
  • Webinar kind: detected and approved type
  • Research summary: key findings compressed
  • Hook options: 5-10 distinct angles presented
  • Selected hook: chosen angle with reasoning
  • Ready for production: boolean gate status
  • Files saved to: resolved paths for brief, research-context, hook-selected
  • Next recommended action: typically "proceed to producer" or "continue discovery"

© pawbytes, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (references) in src/webinar/paw-wbc-agent-discovery of pawbytes/skill-suites.

  • SKILL.md
  • references/frameworks-index.csv
  • references/frameworks/hook-generation.md
  • references/frameworks/research-compression.md
  • references/frameworks/research-methodology.md
  • references/frameworks/webinar-kinds-taxonomy.md

Open the folder on GitHubat commit 547a6df

Compare with similar skills

Paw Wbc Agent Discovery 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.

Paw Wbc Agent Discovery compared with similar skills
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GitHub Deep Researchbytedance/deer-flow84k4 repos~1.3kAutomated safety check: PassMIT
Nature Paper CardYuan1z0825/nature-skills47k2 repos~2.1kAutomated safety check: PassApache-2.0
Content Research Writerweapp-tailwindcss/weapp-tailwindcss1.9k25 repos~3.5kAutomated safety check: PassMIT
Last30daysmvanhorn/last30days-skill64k—~7.9kAutomated safety check: NotesMIT

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Questions about Paw Wbc Agent Discovery

What does Paw Wbc Agent Discovery do?

Research-obsessed strategist for webinar discovery. An agent skill from pawbytes/skill-suites. Paw Wbc Agent Discovery is an agent skill from pawbytes/skill-suites. Research-obsessed strategist for webinar discovery.

When should I use Paw Wbc Agent Discovery?

Paw Wbc Agent Discovery fits situations like: webinar research; hook generation; topic validation; audience analysis.

How do I install Paw Wbc Agent Discovery in Claude Code?

Run `npx skills add pawbytes/skill-suites --skill paw-wbc-agent-discovery -a claude-code`. Or copy the skill folder (src/webinar/paw-wbc-agent-discovery in pawbytes/skill-suites) into .claude/skills/paw-wbc-agent-discovery in your project. Claude Code loads it when a task matches its description.

How do I install Paw Wbc Agent Discovery in Codex?

Run `npx skills add pawbytes/skill-suites --skill paw-wbc-agent-discovery -a codex`. Or copy the skill folder (src/webinar/paw-wbc-agent-discovery in pawbytes/skill-suites) into .agents/skills/paw-wbc-agent-discovery in your project. Codex loads it when a task matches its description.

Can I use Paw Wbc Agent Discovery 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 pawbytes/skill-suites --skill paw-wbc-agent-discovery -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/paw-wbc-agent-discovery, .gemini/skills/paw-wbc-agent-discovery, .github/skills/paw-wbc-agent-discovery and .opencode/skills/paw-wbc-agent-discovery in your project.

What does Paw Wbc Agent Discovery need to run?

SKILL.md names no scripts, command-line tools or credentials: Paw Wbc Agent Discovery is instructions for the agent only.

Does Paw Wbc Agent Discovery 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 Paw Wbc Agent Discovery safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Paw Wbc Agent Discovery use?

Paw Wbc Agent Discovery is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Paw Wbc Agent Discovery use?

About 2.8k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 7.4k tokens, read only when the agent opens those files.

What are the alternatives to Paw Wbc Agent Discovery?

Skills that share tags, products or a category with Paw Wbc Agent Discovery: Hypothesis Generation (spacering-net/codeg, 3.9k stars), GitHub Deep Research (bytedance/deer-flow, 84k stars), Nature Paper Card (Yuan1z0825/nature-skills, 47k stars) and Content Research Writer (weapp-tailwindcss/weapp-tailwindcss, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Paw Wbc Agent Discovery?

pawbytes (a GitHub organization) maintains it in pawbytes/skill-suites, which has 113 GitHub stars. The repository holds 71 skills in this directory. The repository was last updated on October 3, 2026.

Source: pawbytes/skill-suites on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.