Agent skill

Competitors Analysis

by daymade in daymade/claude-code-skills

Clones and audits competitor repositories into evidence-based intelligence with file:line citations.

MITAuto-check passedResearch & Science

Install Competitors Analysis

skills CLI
$ npx skills add daymade/claude-code-skills --skill competitors-analysis -a claude-code

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

GitHub CLI
$ gh skill install daymade/claude-code-skills competitors-analysis --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/daymade/claude-code-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/competitors-analysis .claude/skills/competitors-analysis && 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
competitors-analysis
GitHub stars
1.4k
Token cost
~2.4k tokens
SKILL.md length
984 words
Files
4 (incl. scripts, references)
Skills in repo
103
Repo updated
First seen
Licence
MIT

At a glance

Clones and audits competitor repositories into evidence-based intelligence with file:line citations.

  • Works in 2 steps: Repository evidence: clone or update the… → Landscape synthesis: summarize…
  • Track competitors
  • SKILL.md covers Stop Gate — required input…, Entry Router, Durable Source Layout and Preflight, plus 7 more sections
  • Runs Shell scripts from its folder; calls git and gh; reaches github.com

What it does

Competitors Analysis is an agent skill from daymade/claude-code-skills. Clones and audits competitor repositories into evidence-based intelligence with file:line citations. Use to track competitors, add a competitor repo, review competitor code, compare capabilities, build a competitor landscape, or check for code updates: 竞品分析 / 竞品 / competitor scan / analyze competitor / compare with X / latest competitor code. Not for market research without code (use deep-research).

Its SKILL.md is about 2.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/analysis_checklist.md`, `references/profile_template.md` and `scripts/update-competitors.sh`).

It sits in Research & Science, covering Market research, Deep research and Citation management. The repository describes itself as: Professional Claude Code skills marketplace featuring production-ready skills for enhanced development workflows. The licence is MIT.

When your agent uses it

  • Track competitors
  • Add a competitor repo
  • Review competitor code
  • Compare capabilities

Example prompts

  • “Use the competitors-analysis skill to clone and audits competitor repositories into evidence-based intelligence with file:line citations”
  • “/competitors-analysis”

Requirements

  • A Bash shell

Workflow steps

2 steps, taken from the first numbered list in SKILL.md.

  1. Repository evidence: clone or update the competitor code under the durable
  2. Landscape synthesis: summarize positioning, pricing, strengths, weaknesses,

What it can do on your machine

Read from SKILL.md and the folder at commit 91bed2b. 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

    Ships 1 file in scripts/ (Shell), which the agent can run.

    Shell commands in SKILL.md call:

    • git
    • gh

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • github.com

    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

Competitors Analysis loads about 2.4k tokens when it runs, and up to ~4.3k if it reads all its reference files. Until then it costs about 106 tokens; SKILL.md has 984 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~106
When it runs · the whole SKILL.md, loaded when a task matches
~2.4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.3k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from daymade/claude-code-skills at commit 91bed2b, republished under its MIT licence (© daymade). 984 words, ~2,388 tokens.

Download SKILL.mdSave it as .claude/skills/competitors-analysis/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
competitors-analysis
description
Clones and audits competitor repositories into evidence-based intelligence with file:line citations. Use to track competitors, add a competitor repo, review competitor code, compare capabilities, build a competitor landscape, or check for code updates: 竞品分析 / 竞品 / competitor scan / analyze competitor / compare with X / latest competitor code. Not for market research without code (use deep-research).
context
fork
agent
general-purpose
argument-hint
[product-name] [competitor-url-or-search-query]

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.

Stop Gate — required input (read this first)

This skill runs as context: fork and cannot ask the user anything. The "ask if missing" pattern below therefore does not apply to you. Enforce this hard gate as your very first action:

If the caller did not pass an explicit product/market target for THIS invocation, STOP immediately. Report back: "competitors-analysis needs an explicit product-name or market; none was provided, and as a background fork I cannot ask — aborting rather than inventing a target." Then exit.

Do not:

  • invent or infer a target — a plausible task you generated yourself is still fabricated, not the user's;
  • run ls on $COMPETITORS_BASE to pick an existing product directory as your target;
  • fall through to Discover mode to fill the gap.

A target counts as "provided" only if it came from the caller's request/arguments this invocation — not from a directory name on disk, not from your own reasoning.

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 (in context: fork you cannot ask — the Stop Gate above already handled the missing-target case; if you reached here, a target was provided). 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 <url>"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 caller named a product directory this invocation and it already exists on disk, use it as the source of truth and do not re-clone elsewhere. Never adopt an existing product directory the caller did not name this invocation — that is exactly how a target-less fork silently picks up an unrelated project (2026-09-20 incident: a no-arg fork fabricated an "A2A market" task and ratified it by reusing the on-disk agent-communication dir for 1h23m).

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.

Show full SKILL.md (356 more words)Show less

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.

© daymade, 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 3 other files (scripts, references) in competitors-analysis of daymade/claude-code-skills.

  • SKILL.md
  • references/analysis_checklist.md
  • references/profile_template.md
  • scripts/update-competitors.sh

Open the folder on GitHubat commit 91bed2b

Compare with similar skills

Competitors Analysis 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.

Competitors Analysis compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Competitors Analysis this skilldaymade/claude-code-skills1.4k—~2.4kAutomated safety check: PassMIT
Bmad Deep Recondelorenj/mcp-server-trello445—~2.3kAutomated safety check: PassMIT
Deep Research WorkflowTokenRhythm/opensquilla7.1k—~1.3kAutomated safety check: PassApache-2.0
Deep Researchsanjay3290/ai-skills43110 repos~683Automated safety check: NotesApache-2.0
Academic Research Suite for CodexImbad0202/academic-research-skills-codex12k—~12kAutomated safety check: PassCustom licence
Deep Research Literature SurveyHKUSTDial/Supervisor-Skills8.5k—~2.4kAutomated safety check: PassCC-BY-NC-SA-4.0

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Questions about Competitors Analysis

What does Competitors Analysis do?

Clones and audits competitor repositories into evidence-based intelligence with file:line citations. Competitors Analysis is an agent skill from daymade/claude-code-skills. Clones and audits competitor repositories into evidence-based intelligence with file:line citations.

When should I use Competitors Analysis?

Competitors Analysis fits situations like: track competitors; add a competitor repo; review competitor code; compare capabilities.

How do I install Competitors Analysis in Claude Code?

Run `npx skills add daymade/claude-code-skills --skill competitors-analysis -a claude-code`. Or copy the skill folder (competitors-analysis in daymade/claude-code-skills) into .claude/skills/competitors-analysis in your project. Claude Code loads it when a task matches its description.

How do I install Competitors Analysis in Codex?

Run `npx skills add daymade/claude-code-skills --skill competitors-analysis -a codex`. Or copy the skill folder (competitors-analysis in daymade/claude-code-skills) into .agents/skills/competitors-analysis in your project. Codex loads it when a task matches its description.

Can I use Competitors Analysis 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 daymade/claude-code-skills --skill competitors-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/competitors-analysis, .gemini/skills/competitors-analysis, .github/skills/competitors-analysis and .opencode/skills/competitors-analysis in your project.

What does Competitors Analysis need to run?

Going by SKILL.md and its folder, Competitors Analysis needs a shell for the scripts in its folder and the command-line tools its instructions call (git and gh). Our summary lists: A Bash shell.

Does Competitors Analysis access the network?

SKILL.md names 1 domain. In commands or code: github.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Competitors Analysis 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Competitors Analysis use?

Competitors Analysis 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 Competitors Analysis use?

About 2.4k tokens (SKILL.md is roughly 9.6k 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 2k tokens, read only when the agent opens those files.

What are the alternatives to Competitors Analysis?

Skills that share tags, products or a category with Competitors Analysis: Bmad Deep Recon (delorenj/mcp-server-trello, 445 stars), Deep Research Workflow (TokenRhythm/opensquilla, 7.1k stars), Deep Research (sanjay3290/ai-skills, 431 stars) and Academic Research Suite for Codex (Imbad0202/academic-research-skills-codex, 12k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Competitors Analysis?

daymade (a GitHub user) maintains it in daymade/claude-code-skills, which has 1,444 GitHub stars. The repository holds 103 skills in this directory. The repository was last updated on October 8, 2026.

Source: daymade/claude-code-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.