>- 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 cite their source and volatility.
npx skills add https://github.com/daymade/claude-code-skills --skill competitors-analysis
Build competitor intelligence that can be shared, re-run, and audited later. This
skill has two layers:
competitors workspace, then cite facts from actual files and commits.
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.
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 intent | Mode | What to do |
|---|---|---|
| "find competitors", "竞品有哪些", broad market query | Discover | Search GitHub and web sources, shortlist candidates, clone only relevant repositories |
| "add competitor <url>" | Ingest | Clone the repository, record remote + commit, then produce a first profile |
| "analyze competitor", "review this repo" | Profile | Update or clone locally, read code, write a cited technical profile |
| "compare", "landscape", "opportunities" | Landscape | Ensure each competitor has a profile, then synthesize gaps and opportunities |
| "latest code", "有没有更新" | Update | Pull/fetch existing competitors and report changed commits before analysis |
Use a durable workspace, not /tmp. The default base is:
COMPETITORS_BASE="${COMPETITORS_BASE:-$HOME/workspace/competitors}"
Directory convention:
$COMPETITORS_BASE/
└── {product-slug}/
├── {owner-repo}/
└── ...
Use owner-repo for GitHub repositories so forks and similarly named projects do
not collide. If the user's machine already has a product directory, use it as the
source of truth and do not re-clone elsewhere.
Before analysis, establish these facts from commands, not memory:
repo="$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:
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.
Use gh search repos for GitHub repository discovery. Search multiple query
phrases; do not trust one keyword.
gh search repos "product keywords" \
--limit 30 \
--archived=false \
--json fullName,url,description,stargazersCount,forksCount,openIssuesCount,language,pushedAt,updatedAt,defaultBranch
For each candidate, record:
| Field | Source |
|---|---|
| Repository name and URL | gh search repos / gh repo view |
| Description | GitHub API or README line citation after clone |
| Activity | pushedAt, latest commit, release notes if present |
| Stars/forks/issues | GitHub API with retrieval date |
| Why it is relevant | user'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.
Read files in this order and capture exact sources:
package.json, pyproject.toml, Cargo.toml, go.mod, orequivalent.
main, bin, scripts, src/, app/, packages/.domain-specific modules.
Use nl -ba <file> or an editor with line numbers before citing. Every technical
claim about implementation needs file:line evidence.
For a single competitor, use references/profile_template.md.
For a landscape summary, use this structure:
# {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 |
|---|---|---|---|
| Claim type | Required evidence |
|---|---|
| Dependency/framework/version | Config file line citation |
| Feature support | README/docs line citation plus code citation when technical |
| Parser/export/storage behavior | Code line citation |
| Pricing/cloud-hosted claim | Official page citation with retrieval date |
| Popularity/activity | GitHub API/page citation with retrieval date |
| Opportunity judgment | Evidence rows it derives from plus explicit confidence |
Do not write unsupported technical claims. Avoid these patterns unless they appear
inside an explicit "bad example" block:
| Pattern | Why |
|---|---|
| "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 numbers | Cannot be audited later |
When evidence is unavailable, write 待验证 and state the exact next check that
would verify it.
Before finishing, run the checks in references/analysis_checklist.md:
$COMPETITORS_BASE/{product-slug}/.are code facts.
Use scripts/update-competitors.sh as the starting point for durable competitor
repository management:
COMPETITORS_BASE="$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.
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.
A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).
Extracts and analyzes competitors' ads from ad libraries (Facebook, LinkedIn, etc.) to understand what messaging, problems, and creative approaches are working. Helps inspire and improve your own ad campaigns.
Identifies high-quality leads for your product or service by analyzing your business, searching for target companies, and providing actionable contact strategies. Perfect for sales, business development, and marketing professionals.
Analyzes your recent Claude Code chat history to identify coding patterns, development gaps, and areas for improvement, curates relevant learning resources from HackerNews, and automatically sends a personalized growth report to your Slack DMs.
Complete App Store Optimization (ASO) toolkit for researching, optimizing, and tracking mobile app performance on Apple App Store and Google Play Store
NGS analysis toolkit. BAM to bigWig conversion, QC (correlation, PCA, fingerprints), heatmaps/profiles (TSS, peaks), for ChIP-seq, RNA-seq, ATAC-seq visualization.
Materials science toolkit. Crystal structures (CIF, POSCAR), phase diagrams, band structure, DOS, Materials Project integration, format conversion, for computational materials science.
Transforms vague UI ideas into polished, Stitch-optimized prompts. Enhances specificity, adds UI/UX keywords, injects design system context, and structures output for better generation results.
Take daymade/competitors-analysis from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.