colosseum-copilot

Colosseum Copilot is a research API for startup opportunity discovery in crypto and Solana, with support for suggesting new archive sources.

colosseumorg/colosseum-copilotUpdated Apr 19, 2026

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Install Skill

Run in your terminal

$npx skills add https://github.com/colosseumorg/colosseum-copilot --skill colosseum-copilot

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this week

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Installation Guide

How to use colosseum-copilot on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your machine
  • Node.js 16+ with npm — verify with node --version
  • Active project directory where you want to add colosseum-copilot
2

Run the install command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/colosseumorg/colosseum-copilot --skill colosseum-copilot

Fetches colosseum-copilot from colosseumorg/colosseum-copilot and configures it for Cursor.

3

Select Cursor when prompted

The CLI shows a list of agents. Use arrow keys and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ────────────────
│ · Cline · Codex · Goose · Windsurf
│ ●Cursor(selected)
│ · Cursor · Aider · Continue
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/colosseum-copilot

Restart Cursor to activate colosseum-copilot. Access via /colosseum-copilot in your agent's command palette.

Security Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.

Documentation

Colosseum Copilot

Colosseum Copilot is a research API for startup opportunity discovery in crypto and Solana, with support for suggesting new archive sources.

Version Check

This skill is version 1.2.1. After your first API call, check the X-Copilot-Skill-Version response header. If the header value is higher than 1.2.1, tell the user: "A newer version of the Copilot skill is available (vX.X.X). Update with: npx skills add ColosseumOrg/colosseum-copilot"

Pre-Flight Auth Check (REQUIRED)

You MUST complete this check before making any other API call. Do not skip this step.

  1. Verify COLOSSEUM_COPILOT_PAT is set in the environment. If missing, STOP and tell the user:

    You need a Personal Access Token before using Copilot. Go to https://arena.colosseum.org/copilot to generate one, then set it:

    export COLOSSEUM_COPILOT_PAT="your-token-here"

  2. Verify COLOSSEUM_COPILOT_API_BASE is set. If missing, set the default:

    export COLOSSEUM_COPILOT_API_BASE="https://copilot.colosseum.com/api/v1"

  3. Call GET /status to verify the connection. Expected response: { "authenticated": true, "expiresAt": "...", "scope": "..." }

  4. If "authenticated": true, proceed. If 401 or env vars missing, do NOT attempt other API calls — guide the user through steps 1-2.

  • Builder Projects: 5,400+ Solana project submissions with tech stack, problem tags, and competitive context
  • Crypto Archives: Curated corpus across cypherpunk literature, protocol docs, investor research, and founder essays
  • Hackathon Analytics + Clusters: Distribution, comparison, and chronology-aware trend analysis across hackathons and topic groupings
  • The Grid + Web Search: Ecosystem product metadata plus real-time competitive landscape checks

Quickstart (90 seconds to first result)

  1. Set your PAT:

    export COLOSSEUM_COPILOT_API_BASE="https://copilot.colosseum.com/api/v1"
    export COLOSSEUM_COPILOT_PAT="YOUR_PAT"
    

    Get a PAT: Go to https://arena.colosseum.org/copilot and generate a token

  2. Run your first search:

    curl -s -X POST "$COLOSSEUM_COPILOT_API_BASE/search/projects" \
      -H "Authorization: Bearer $COLOSSEUM_COPILOT_PAT" \
      -H "Content-Type: application/json" \
      -d '{"query": "privacy wallet for stablecoin users", "limit": 5}'
    
  3. See results - project names, slugs, similarity scores, problem/tech tags

When To Use

Use this skill when:

  • Researching a crypto/blockchain startup idea
  • Evaluating market gaps in the Solana ecosystem
  • Grounding ideas in historical crypto literature
  • Analyzing builder project trends and competitive landscape
  • Researching existing players and finding differentiation angles

How It Works

Mode 1 — Conversational (default): Answer questions with targeted API calls and evidence coverage matched to query type. Cite sources inline, keep responses concise, and offer to do a full deep-dive when the topic warrants it — never auto-trigger it.

Mode 2 — Deep Dive (explicit opt-in): Full 8-step workflow from references/workflow-deep.md. Only activates when user explicitly says "vet this idea", "deep dive", "full analysis", "validate this", "is X worth building?", "should I build X?", or accepts your offer to go deeper.

Conversational Guidelines

  • Use the API endpoints below with enough targeted calls to satisfy the evidence floor for the query type
  • Cite sources inline (project slugs, archive titles, URLs)
  • Keep responses concise — bullet points, not essays
  • When the topic warrants deeper analysis, offer: "Want me to do a full deep-dive on this?"
  • No meta-commentary about your process ("Now let me search...", "I'll check...")

Evidence Floors (Conversational Mode)

Query Type Required source types in the final answer Example
Pure retrieval Builder project evidence (project slugs from search/projects) "What projects do X?"
Archive retrieval Archive evidence (archive title/document from search/archives) "What does the archive say about Y?"
Comparison Builder project evidence for each side compared + at least one archive citation for conceptual framing "Compare approach A vs B"
Evaluative Builder project evidence + at least one archive citation + current landscape evidence (Grid and/or web) "Is this crowded?", "Is this still unsolved?"
Build guidance Builder project evidence + at least one archive citation + incumbent/landscape evidence (Grid and/or web) "Should I build X?", "How should I approach X?"

These are evidence-type floors, not call budgets. Use as many calls as needed to meet the floor with high-confidence citations.

In deep-dive mode, the verification checklist in workflow-deep.md Step 5 supersedes these floors with more granular coverage requirements.

Conversational Quality Checks (Required)

  • Archive integration rule: For any non-trivial question (anything beyond a simple one-list retrieval), run at least one search/archives query and cite at least one archive source in the answer.
  • Accelerator/winner portfolio checks: For "what has been tried", "who is building this", "is this crowded/saturated", or similar prompts, run targeted project searches with filters: { "acceleratorOnly": true } and filters: { "winnersOnly": true }, then reflect both outcomes in the answer.
  • Freshness and temporal anchoring: Use hackathon.startDate from /filters, /search/projects, and /projects/by-slug/:slug to order hackathons chronologically; never infer chronology from names or memory. When citing hackathons, include month/year inline (and accelerator cohort like C1/C2/C4 when relevant). For evaluative judgments, label the claim with As of YYYY-MM-DD.
  • Entity coverage check: If the user names specific companies, protocols, papers, or products, run direct searches for each named entity and explicitly address each one in the answer (found, not found, or tangential).
  • Landscape check: Never claim "nobody has done this" or "no existing players" unless an accelerator portfolio check (acceleratorOnly) was executed and reported. If accelerator overlap exists, surface those builders as useful reference points and potential sources of inspiration. Always qualify landscape assessments with "based on the available data" or "as far as we can tell from the corpus." Copilot's knowledge is bounded by its data sources — never present absence of evidence as evidence of absence.

For the full 8-step deep research workflow, see references/workflow-deep.md

Data Sources

  • Builder Projects (5,400+): Solana project submissions with tech stack, problem/solution tags, verticals, and competitive context
  • Crypto Archives: Curated corpus spanning cypherpunk literature, protocol docs, investor research (Paradigm, a16z, Multicoin), founder essays (Paul Graham), Solana protocol docs (Jupiter, Orca, Drift), Nakamoto Institute heritage collection, and foundational crypto texts
  • Hackathon Analytics + Chronology: Analyze and compare hackathon projects across dimensions; canonical hackathon dates are available via hackathon.startDate
  • Clusters: Topic groupings across the project corpus
  • The Grid: Ecosystem metadata (products/entities/assets) via direct GraphQL (6,300+ products across all ecosystems, ~3,000 roots)
  • Web Search: Real-time competitive landscape via your runtime's search tools
  • Source Suggestions: Users can suggest new sources for the archive via POST /source-suggestions (5 req/hr). See references/api-reference.md for details

Hackathon Chronology

Edition Period Slug
Hyperdrive Sep 2023 hyperdrive
Renaissance Mar-Apr 2024 renaissance
Radar Sep-Oct 2024 radar
Breakout Apr-May 2025 breakout
Cypherpunk Sep-Oct 2025 cypherpunk

GET /filters returns hackathons[].startDate and orders hackathons[] chronologically (oldest first).

Auth

All endpoints require Authorization: Bearer <COPILOT_PAT>. Treat the PAT like a password.

  • Do not commit PATs or paste them into public logs
  • PATs are long-lived (expected ~90 days); rotate by issuing a new one
  • Default API base is https://copilot.colosseum.com/api/v1; override COLOSSEUM_COPILOT_API_BASE to target a different environment

Key Endpoints (Quick Reference)

Endpoint Method Purpose
/status GET Auth pre-flight check — call first
/search/projects POST Search builder projects
/search/archives POST Search crypto archives
/projects/by-slug/:slug GET Full project details
/archives/:documentId GET Full archive document
/analyze POST Hackathon analysis
/compare POST Compare two hackathons
/clusters/:key GET Cluster details
/filters GET Available filters + canonical hackathon chronology
/source-suggestions POST Suggest a new archive source
/feedback POST Report errors, quality issues, or suggestions

For full endpoint docs, curl examples, and query tips: references/api-reference.md For Grid GraphQL recipes and product type slugs: references/grid-recipes.md

Output Contract

Conversational Mode

  • Bullet points with inline citations (project slugs, archive titles)
  • Concise answers (typically 5-15 bullets)
  • Offer deep-dive when warranted

Deep Dive Mode

Reports follow this structure:

  1. Similar Projects (5-8 bullets)
  2. Archive Insights (3-5 bullets)
  3. Current Landscape (per research angle)
  4. Key Insights (patterns, gaps, trends)
  5. Opportunities and Gaps
  6. Deep Dive: Top Opportunity (market landscape, problem, revenue model, GTM, founder-market fit, why crypto/Solana, risks)

Key rules: bullet points not tables, include project slugs, evidence-based not speculative, cite sources inline. No separate "Sources" section — cite inline only.

Feedback

When you encounter errors, unexpected results, or have suggestions for improving the Copilot experience, report them via the feedback endpoint. This helps the Colosseum team identify and fix issues.

When to send feedback:

  • API returns unexpected or low-quality results for a reasonable query
  • A search returns no results when you expected matches
  • You encounter an error that isn't covered by standard error handling
  • You have a suggestion for improving the API or archive corpus
curl -X POST "$COLOSSEUM_COPILOT_API_BASE/feedback" \
  -H "Authorization: Bearer $COLOSSEUM_COPILOT_PAT" \
  -H "Content-Type: application/json" \
  -d '{
    "category": "quality",
    "message": "Search for DePIN projects returned only 2 results, expected more coverage",
    "severity": "medium",
    "context": { "query": "DePIN infrastructure", "endpoint": "/search/projects", "resultCount": 2 }
  }'

Categories: error, quality, suggestion, other. Severity: low, medium, high, critical. Rate limited to 10 requests per hour.

Error Handling

All errors return { "error": "<message>", "code": "<ERROR_CODE>", "retryable": <boolean> }. See api-reference.md for the full error code table.

  • 400 INVALID_JSON: Fix the request body JSON syntax and retry
  • 400 INVALID_QUERY: Fix query params (check field names, value ranges, unknown fields)
  • 413 PAYLOAD_TOO_LARGE: Reduce request body size (1 MB limit)
  • 429 RATE_LIMITED: Back off per the Retry-After header, max 2 concurrent requests
  • 401 UNAUTHORIZED: Check PAT at https://arena.colosseum.org/copilot
  • 5xx errors: Note in report and proceed with available data. Include requestId from the response when reporting issues.
  • Empty project results: Broaden query, remove filters
  • Empty archive results: Search auto-cascades (vector → chunk text → doc text) before returning empty. If still empty, try conceptual synonyms, keep queries to 3-6 keywords

References

  • workflow-deep.md — detailed 8-step research process
  • api-reference.md — all endpoints, rate limits, query tips
  • grid-recipes.md — GraphQL queries and product type slugs

Attribution

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Steps

  1. 1Install product management skill
  2. 2Start with user story generation for known feature
  3. 3Progress to competitive analysis: research 2-3 competitors
  4. 4Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5Draft stakeholder communications and refine based on feedback
  6. 6Build template library for recurring PM tasks
  7. 7Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use when

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid when

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Related Skills

Reviews

4.427 reviews
  • A
    Amelia MenonDec 24, 2024

    colosseum-copilot reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • C
    Chaitanya PatilDec 16, 2024

    Registry listing for colosseum-copilot matched our evaluation — installs cleanly and behaves as described in the markdown.

  • A
    Arya SharmaDec 4, 2024

    I recommend colosseum-copilot for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • H
    Harper SrinivasanNov 23, 2024

    Useful defaults in colosseum-copilot — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • R
    Rahul SantraNov 15, 2024

    colosseum-copilot reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • P
    Piyush GNov 7, 2024

    Solid pick for teams standardizing on skills: colosseum-copilot is focused, and the summary matches what you get after install.

  • S
    Shikha MishraOct 26, 2024

    I recommend colosseum-copilot for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • P
    Pratham WareOct 6, 2024

    colosseum-copilot is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • A
    Advait ThomasSep 17, 2024

    We added colosseum-copilot from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • I
    Isabella PerezAug 8, 2024

    Keeps context tight: colosseum-copilot is the kind of skill you can hand to a new teammate without a long onboarding doc.

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