Competitors Analysis logo

Competitors Analysis

CommunityPopular
daymade
competitors-analysis

Discover, clone, update, and analyze competitor repositories with evidence-based competitive intelligence. Use when tracking competitors, reviewing competitor source code, adding a competitor repository, comparing product capabilities, building a competitor landscape, checking whether competitor code changed, or when the user says "竞品分析", "竞品", "competitor scan", "latest competitor code", "analyze competitor", or "compare with X". Repository-backed findings must come from local cloned code with file:line citations; market-landscape claims must cite their source and volatility.

Overview

Publisherdaymade
Repositoryclaude-code-skills
Skill namecompetitors-analysis
Stars
1.4K
Forks
219
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by daymade on GitHub. Read the source before you install it.

Installation

Install the Competitors Analysis AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/daymade/claude-code-skills.git /tmp/claude-code-skills
mkdir -p .claude/skills
cp -r /tmp/claude-code-skills/competitors-analysis .claude/skills/competitors-analysis
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Competitors Analysis in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Competitors Analysis on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Competitors Analysis is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Competitors Analysis

Build competitor intelligence that can be shared, re-run, and audited later. This skill has two layers:

  1. Repository evidence: clone or update the competitor code under the durable competitors workspace, then cite facts from actual files and commits.
  2. Landscape synthesis: summarize positioning, pricing, strengths, weaknesses, gaps, and opportunities, but only after separating sourced facts from judgment.

This skill intentionally subsumes lightweight "competitor scan" workflows. A scan is useful for the landscape table, but it is not enough for technical conclusions.

Entry Router

If the user's request is missing the product/market or target customer segment, ask for that context before synthesizing positioning or opportunity claims. Known competitors are optional; if absent, use Discover mode.

Use the user's wording to choose the path:

User intentModeWhat to do
"find competitors", "竞品有哪些", broad market queryDiscoverSearch GitHub and web sources, shortlist candidates, clone only relevant repositories
"add competitor "IngestClone the repository, record remote + commit, then produce a first profile
"analyze competitor", "review this repo"ProfileUpdate or clone locally, read code, write a cited technical profile
"compare", "landscape", "opportunities"LandscapeEnsure each competitor has a profile, then synthesize gaps and opportunities
"latest code", "有没有更新"UpdatePull/fetch existing competitors and report changed commits before analysis

Durable Source Layout

Use a durable workspace, not /tmp. The default base is:

bash
COMPETITORS_BASE="${COMPETITORS_BASE:-$HOME/workspace/competitors}"

Directory convention:

text
$COMPETITORS_BASE/
└── {product-slug}/
    ├── {owner-repo}/
    └── ...

Use owner-repo for GitHub repositories so forks and similarly named projects do not collide. If the user's machine already has a product directory, use it as the source of truth and do not re-clone elsewhere.

Preflight

Before analysis, establish these facts from commands, not memory:

bash
repo="$COMPETITORS_BASE/{product-slug}/{owner-repo}"
test -d "$repo/.git"
git -C "$repo" remote -v
git -C "$repo" fetch --all --prune
git -C "$repo" log -1 --format='%H%x09%cI%x09%s'

If the repository is missing, clone it first. Prefer SSH for GitHub when possible:

bash
mkdir -p "$COMPETITORS_BASE/{product-slug}"
git clone --depth 1 <git-ssh-url> "$COMPETITORS_BASE/{product-slug}/{owner-repo}"

If SSH fails for a public repository, report the failure and retry with the repository's HTTPS URL only when that keeps the work moving.

Discovery Workflow

Use gh search repos for GitHub repository discovery. Search multiple query phrases; do not trust one keyword.

bash
gh search repos "product keywords" \
  --limit 30 \
  --archived=false \
  --json fullName,url,description,stargazersCount,forksCount,openIssuesCount,language,pushedAt,updatedAt,defaultBranch

For each candidate, record:

FieldSource
Repository name and URLgh search repos / gh repo view
DescriptionGitHub API or README line citation after clone
ActivitypushedAt, latest commit, release notes if present
Stars/forks/issuesGitHub API with retrieval date
Why it is relevantuser's product scope + repository evidence

Clone only candidates that are relevant to the user's product or analysis goal. For broad markets, first present a shortlist with evidence and then analyze the strongest set.

Repository Fact Gathering

Read files in this order and capture exact sources:

  1. Project metadata: package.json, pyproject.toml, Cargo.toml, go.mod, or equivalent.
  2. README and docs: positioning, screenshots, installation, pricing links.
  3. Entry points: main, bin, scripts, src/, app/, packages/.
  4. Core implementation: renderer, parser, storage, export, sync, auth, API, or domain-specific modules.
  5. Tests and fixtures: they often reveal supported data structures and edge cases.
  6. Releases/changelog: current direction and recent changes.

Use nl -ba <file> or an editor with line numbers before citing. Every technical claim about implementation needs file:line evidence.

Report Structure

For a single competitor, use references/profile_template.md.

For a landscape summary, use this structure:

markdown
# {Product} Competitor Landscape

## Source Register
| Competitor | Local path | Remote | Commit | Retrieved |
|---|---|---|---|---|

## Positioning
| Competitor | User segment | Primary promise | Source |
|---|---|---|---|

## Product And Technical Comparison
| Dimension | Competitor A | Source | Competitor B | Source | Our product | Source |
|---|---|---|---|---|---|---|

## Strengths
| Competitor | Strength | Evidence | Why it matters |
|---|---|---|---|

## Weaknesses And Gaps
| Competitor | Gap | Evidence | Opportunity |
|---|---|---|---|

## Opportunities
| Opportunity | Evidence base | Product implication | Confidence |
|---|---|---|---|

## Risks And Assumptions
| Item | What is known | What still needs verification | Next check |
|---|---|---|---|

Evidence Rules

Required

Claim typeRequired evidence
Dependency/framework/versionConfig file line citation
Feature supportREADME/docs line citation plus code citation when technical
Parser/export/storage behaviorCode line citation
Pricing/cloud-hosted claimOfficial page citation with retrieval date
Popularity/activityGitHub API/page citation with retrieval date
Opportunity judgmentEvidence rows it derives from plus explicit confidence

Forbidden

Do not write unsupported technical claims. Avoid these patterns unless they appear inside an explicit "bad example" block:

PatternWhy
"推测", "可能", "应该", "大概", "似乎"Blurs evidence and judgment
"未公开", "未披露"Pretends to know disclosure status
"architecture, inferred from UI"Technical architecture must come from code
Unsourced numbersCannot be audited later

When evidence is unavailable, write 待验证 and state the exact next check that would verify it.

Output Quality Bar

Before finishing, run the checks in references/analysis_checklist.md:

  • Local repository exists under $COMPETITORS_BASE/{product-slug}/.
  • Remote URL and latest commit are recorded.
  • Each technical claim has a file:line citation.
  • Market facts have a source and retrieval date.
  • Landscape judgments are separated from facts.
  • The final answer names gaps, opportunities, and risks without pretending they are code facts.

Script

Use scripts/update-competitors.sh as the starting point for durable competitor repository management:

bash
COMPETITORS_BASE="$HOME/workspace/competitors" \
PRODUCT_NAME="{product-slug}" \
./scripts/update-competitors.sh status

./scripts/update-competitors.sh discover "claude code viewer"
./scripts/update-competitors.sh clone-url https://github.com/org/repo
./scripts/update-competitors.sh pull

The script is a template. For a long-running product, copy it into that product's own repo or operations directory and fill the persistent competitor list.

Relationship To Product Analysis

product-analysis may invoke this skill for compare mode. Keep this skill focused on competitor discovery, repository evidence, and competitive synthesis. Do not turn it into a general product audit orchestrator.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Competitors Analysis AI skill do?

Discover, clone, update, and analyze competitor repositories with evidence-based competitive intelligence. Use when tracking competitors, reviewing competitor source code, adding a competitor repository, comparing product capabilities, building a competitor landscape, checking whether competitor code changed, or when the user says "竞品分析", "竞品", "competitor scan", "latest competitor code", "analyze competitor", or "compare with X". Repository-backed findings must come from local cloned code with file:line citations; market-landscape claims must cite their source and volatility.

Why use Competitors Analysis on TypingMind?

Because you install it once and use it with any model. Competitors Analysis is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Competitors Analysis in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/daymade/claude-code-skills/tree/main/competitors-analysis. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Competitors Analysis?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Competitors Analysis?

As many as you like. As long as a model supports skills, you can use Competitors Analysis with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Competitors Analysis AI skill free?

Yes. It is published on GitHub by daymade under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇