Is This A Problem
anthropics/claude-for-legal
Fast "is this a problem?" answer for the quick Slack question — pattern-matches against your calibration.
Trigger: vague/unfocused request or solution-without-problem.
$ npx skills add hashgraph-online/awesome-codex-plugins --skill discover -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins discover --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/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/epicsagas/epic-harness/skills/discover .claude/skills/discover && 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 "discover" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/epicsagas/epic-harness/skills/discover into .claude/skills/discover/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "discover", 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/hashgraph-online/awesome-codex-plugins/tree/main/plugins/epicsagas/epic-harness/skills/discoverType 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 hashgraph-online/awesome-codex-plugins --skill discover -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins discover --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/epicsagas/epic-harness/skills/discover .agents/skills/discover && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "discover" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/epicsagas/epic-harness/skills/discover into .agents/skills/discover/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "discover", 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 hashgraph-online/awesome-codex-plugins --skill discover -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins discover --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/epicsagas/epic-harness/skills/discover .cursor/skills/discover && 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 "discover" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/epicsagas/epic-harness/skills/discover into .cursor/skills/discover/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "discover", 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/hashgraph-online/awesome-codex-plugins.git --path plugins/epicsagas/epic-harness/skills/discover--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 hashgraph-online/awesome-codex-plugins --skill discover -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins discover --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/epicsagas/epic-harness/skills/discover .gemini/skills/discover && 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 "discover" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/epicsagas/epic-harness/skills/discover into .gemini/skills/discover/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "discover", 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 hashgraph-online/awesome-codex-plugins discoverInstalls 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 hashgraph-online/awesome-codex-plugins --skill discover -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/epicsagas/epic-harness/skills/discover .github/skills/discover && 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 "discover" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/epicsagas/epic-harness/skills/discover into .github/skills/discover/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "discover", 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 hashgraph-online/awesome-codex-plugins --skill discover -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins discover --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/epicsagas/epic-harness/skills/discover .opencode/skills/discover && 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 "discover" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/epicsagas/epic-harness/skills/discover into .opencode/skills/discover/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "discover", 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.
discoverTrigger: vague/unfocused request or solution-without-problem.
Discover is an agent skill from hashgraph-online/awesome-codex-plugins. Trigger: vague/unfocused request or solution-without-problem. Also invoked via /discover command. Reframes goal before acting.
Its SKILL.md is about 2.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
The repository describes itself as: A curated list of awesome OpenAI Codex / ChatGPT plugins, skills, and resources. The 1 Codex Marketplace. See live plugins at: https://hol.org/plugins/best-codex-plugins. The licence is Apache-2.0.
6 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 78497e5. It shows what the files ask for, not the result of running them.
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.
No scripts in the folder and no shell commands in SKILL.md (its code samples are bash and markdown).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Discover loads about 2.5k tokens when it runs. Until then it costs about 34 tokens; SKILL.md has 1,125 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.
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.
The full file from hashgraph-online/awesome-codex-plugins at commit 78497e5, republished under its Apache-2.0 licence (© hashgraph-online). 1,125 words, ~2,499 tokens.
.claude/skills/discover/SKILL.md (or your agent's skills folder).You are starting the Discover phase. Your job is to help the user articulate what problem they are actually trying to solve, before jumping to solutions or specs.
CRITICAL: Run HARNESS_DIR=$(epic-harness path) first. NEVER use .harness/ in the project directory.
NO SPEC WITHOUT A PROBLEM STATEMENT. Building the wrong thing well is worse than building the right thing poorly.
HARNESS_DIR=$(epic-harness path)$HARNESS_DIR/specs/PROBLEM-*.mdmem_recall with a hint describing the current topic areadecision or pattern nodes related to this domainWhy: Past context prevents re-exploring ground already covered. The knowledge graph connects today's vague request to yesterday's decisions.
Read the user's request carefully. Repeat it back in your own words and ask:
Categorize the request:
| Category | Signal | Example |
|---|---|---|
| Solution without problem | User names a technology or approach | "Add Redis caching" |
| Feature without context | User describes output, not why | "Build a dashboard" |
| Systemic complaint | Broad negative without specifics | "Everything is slow" |
| Vague ambition | Goal with no boundaries | "Make it better" |
| Clear problem | Observable gap stated | "Login fails for 5% of users" |
Why: Categorization determines the probing technique. Misreading the category leads to wrong questions.
Select the technique based on the category identified in Step 1. Ask max 3 questions per round, run max 3 rounds. If the user can't answer or says "I'm not sure", proceed to Frame with what you have.
| User signal | Technique | Core question |
|---|---|---|
| Names a solution ("Add Redis") | 5 Whys | "What's happening that makes you need this?" → repeat |
| Describes a feature without why | JTBD | "What situation makes you need this? What would 'done' look like?" |
| "Everything is broken" | Fishbone | "Which area: People / Process / Technology / Data / Environment?" |
| Vague or contradictory | Socratic | "What specifically do you mean by 'X'?" |
| Has a vision but no path | Done looks like | "When this works perfectly, what do you see?" |
| Uncertain assumptions | Assumption map | "What must be true for this to work?" |
5 Whys — when the user presents a solution without a problem:
User: "Add Redis caching to the API."
→ "What's happening that makes you want caching?"
→ "Why is that slow?"
→ "Why does that query take long?"Stop when you reach an actionable root cause. Max 5 levels.
JTBD (Jobs To Be Done) — when the user describes a feature without context:
User: "Build a dashboard."
→ "What situation makes you need this?"
→ "What would you do with the information right now?"
→ "What would have to be true for you to say 'this solved it'?"Extract job stories: "When [situation], I want [motivation], so I can [outcome]."
Fishbone — when the user has a systemic complaint:
User: "Everything is broken."
→ Walk through categories: People, Process, Technology, Data, Environment
→ "Which of these areas is the biggest contributor?"
→ "Is this on all branches or specific ones?"Map causes across categories, then narrow to the top 1-2.
Socratic Questioning — when the request is vague or contradictory:
User: "Make it more secure." / "I want it to be faster."
→ Clarification: "What specifically do you mean by 'secure' / 'fast'?"
→ Probing assumptions: "What makes you believe this is the issue?"
→ Implications: "If we change X, what happens to Y?"
→ Alternatives: "What other approaches did you consider?""What Does Done Look Like?" — when the user has a vision but no path:
→ "When this is shipped and working perfectly, what specifically do you see?"
→ "What would I click, what output would appear, what would the logs show?"Work backwards from the concrete end state.
Assumption Mapping — when the request depends on uncertain premises:
→ "Let me check what we're assuming must be true for this to work."
→ List 4-5 assumptions, ask which are uncertain.Shaky assumptions become prerequisites.
Each round should narrow the space. If after 2 rounds you have enough to frame, don't force a third.
Why: The right technique extracts the real problem in 2-3 rounds instead of 10 random questions. Technique mismatch wastes rounds and frustrates the user.
Synthesize everything into a structured problem statement:
[Who] experiences [observable problem] when [trigger condition], resulting in [quantified impact]. The desired state is [measurable outcome].
Capture supporting context:
Show the frame to the user and ask: "Does this capture the problem accurately?"
Why: A written problem statement is testable. If you can't write one, you haven't discovered the problem yet.
Once confirmed, save the problem statement:
mkdir -p "$HARNESS_DIR/specs"Write to $HARNESS_DIR/specs/PROBLEM-{timestamp}.md (see Output Format below).
If the user realizes there are multiple problems during probing, address them one at a time. Each problem gets its own file.
Tell the user: "Problem defined. Run /spec to turn this into a buildable specification."
If the user wants to explore further (e.g., they realize there are actually 3 problems), loop back to Step 2 with the new angle.
Why: The transition from problem to spec is natural but explicit. The user owns the decision to move forward.
Auto-trigger (no command needed):
Explicit invocation (/discover):
| Excuse | Rebuttal | What to do instead |
|---|---|---|
| "Let's just start building and figure it out" | Building without a problem is expensive guessing. | Spend 5 minutes framing the problem. It saves hours of rework. |
| "The problem is obvious" | If it were obvious, you'd have a spec, not a vague request. | Write the problem statement. If it's obvious, it takes 30 seconds. |
| "I don't have time for questions" | You don't have time to build the wrong thing. | Run 2 focused rounds, not 10 open-ended ones. |
| "I already told you the problem" | You told me a solution. The problem is why you need that solution. | Ask one "why" question. If the answer reveals the problem, proceed. |
| "Can't you just figure it out from the code?" | Code shows what exists, not what's missing or why it hurts. | Combine code exploration with user context for the full picture. |
| "Let me just show you the bug" | A bug is a symptom, not a problem. Fixing symptoms is whack-a-mole. | Trace the bug to its root cause before jumping to a fix. |
Before claiming the problem is defined, show ALL of these:
"I think I understand" without a written problem statement = guessing.
Save to $HARNESS_DIR/specs/PROBLEM-{timestamp}.md:
---
status: framed
created: {ISO-8601 timestamp}
context: {one-line summary}
---
# Problem: {title}
## Problem Statement
{Who} experiences {observable problem} when {trigger condition}, resulting in {quantified impact}. The desired state is {measurable outcome}.
## Root Cause / Job Story
{5 Whys chain or JTBD job story}
## Constraints
- Timeline: {when is this needed}
- Technology: {stack constraints}
- Scale: {expected load/users}
- Compatibility: {backward-compat requirements}
## Assumptions
- {assumption} — {certain / uncertain}
- {assumption} — {certain / uncertain}
## Out of Scope
- {what this problem explicitly does NOT cover}© hashgraph-online, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in plugins/epicsagas/epic-harness/skills/discover of hashgraph-online/awesome-codex-plugins.
Open the folder on GitHubat commit 78497e5
Discover 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 |
|---|---|---|---|---|---|---|
| Discover this skillhashgraph-online/awesome-codex-plugins | 1.2k | — | ~2.5k | Automated safety check: Pass | Apache-2.0 | |
| Is This A Problemanthropics/claude-for-legal | 9.6k | 2 repos | ~2.3k | Automated safety check: Pass | Apache-2.0 | |
| Discover Pluginsruvnet/ruflo | 74k | — | ~2k | Automated safety check: Notes | MIT | |
| Aas Discoversickn33/agentic-awesome-skills | 47k | 1 repos | ~523 | Automated safety check: Pass | MIT | |
| Opportunity Solution Treephuryn/pm-skills | 27k | — | ~1.1k | Automated safety check: Pass | MIT | |
| Google Cloud Solution Architecturegoogle/skills | 21k | — | ~3.5k | Automated safety check: Pass | Apache-2.0 |
anthropics/claude-for-legal
Fast "is this a problem?" answer for the quick Slack question — pattern-matches against your calibration.
ruvnet/ruflo
Discover and recommend ruflo plugins based on your workflow, installed MCP tools, and current task
sickn33/agentic-awesome-skills
Discover AAS skills for an explicit task and compare their complete instructions without installing them.
phuryn/pm-skills
Build an Opportunity Solution Tree (OST) to structure product discovery — map a desired outcome to opportunities, solutions, and experiments.
google/skills
Interactively discovers requirements and designs holistic, multi-product system architectures, solution blueprints, and deployment recommendations for complex workloads on Google Cloud.
brycewang-stanford/Auto-Empirical-Research-Skills
Discovery phase combining research interviews, literature search, data discovery, and ideation.
hashgraph-online/awesome-codex-plugins
Create original anime-style reaction stickers as looping GIFs and MP4 previews, using generated character pose sheets and timed key poses.
hashgraph-online/awesome-codex-plugins
Manage and query Calibre libraries with the calibredb CLI (local paths or Calibre Content server URLs).
hashgraph-online/awesome-codex-plugins
A skill your agent uses when adding, changing, testing, or debugging Rust HTTP APIs and services, especially when Codex needs black-box integration tests, random-port app startup, real database test…
hashgraph-online/awesome-codex-plugins
Make a studio's game look like something at build time — a cover from a real frame of the game (free), painted covers, backdrops, textures and character plates from image models through the…
hashgraph-online/awesome-codex-plugins
Balance game difficulty, resources, rewards, probability, progression, economies, and dominant strategies.
hashgraph-online/awesome-codex-plugins
Analyze nonfiction manuscripts for reader engagement signals, including heading-level word counts, slow starts, long slogs, weak takeaway titles, value pacing, beta-reader comment dropoff, and…
Trigger: vague/unfocused request or solution-without-problem. Discover is an agent skill from hashgraph-online/awesome-codex-plugins. Trigger: vague/unfocused request or solution-without-problem.
Run `npx skills add hashgraph-online/awesome-codex-plugins --skill discover -a claude-code`. Or copy the skill folder (plugins/epicsagas/epic-harness/skills/discover in hashgraph-online/awesome-codex-plugins) into .claude/skills/discover in your project. Claude Code loads it when a task matches its description.
Run `npx skills add hashgraph-online/awesome-codex-plugins --skill discover -a codex`. Or copy the skill folder (plugins/epicsagas/epic-harness/skills/discover in hashgraph-online/awesome-codex-plugins) into .agents/skills/discover in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add hashgraph-online/awesome-codex-plugins --skill discover -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/discover, .gemini/skills/discover, .github/skills/discover and .opencode/skills/discover in your project.
SKILL.md names no scripts, command-line tools or credentials: Discover is instructions for the agent only.
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.
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.
Discover is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.5k tokens (SKILL.md is roughly 10k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Discover: Is This A Problem (anthropics/claude-for-legal, 9.6k stars), Discover Plugins (ruvnet/ruflo, 74k stars), Aas Discover (sickn33/agentic-awesome-skills, 47k stars) and Opportunity Solution Tree (phuryn/pm-skills, 27k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
hashgraph-online (a GitHub organization) maintains it in hashgraph-online/awesome-codex-plugins, which has 1,242 GitHub stars. The repository holds 686 skills in this directory. The repository was last updated on October 8, 2026.
Source: hashgraph-online/awesome-codex-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.