Agent skill

Competitive Analysis

by ginlix-ai in ginlix-ai/LangAlpha

Competitive landscape analysis: positioning, scorecards, moat assessment, market share trends.

Apache-2.0Auto-check passedMarketing & SEO

Install Competitive Analysis

skills CLI
$ npx skills add ginlix-ai/LangAlpha --skill competitive-analysis -a claude-code

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

GitHub CLI
$ gh skill install ginlix-ai/LangAlpha competitive-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/ginlix-ai/LangAlpha.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/langalpha_research/skills/competitive-analysis .claude/skills/competitive-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
competitive-analysis
GitHub stars
1.8k
Token cost
~3.1k tokens
SKILL.md length
1,676 words
Files
5 (incl. references)
Skills in repo
37
Repo updated
First seen
Licence
Apache-2.0

At a glance

Competitive landscape analysis: positioning, scorecards, moat assessment, market share trends.

  • Works in 10 steps: Identify the industry-defining metrics → Market context → Industry economics → …
  • Competitive analysis
  • SKILL.md covers Reference files, Data standards, Workflow phases and Analysis workflow, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Competitive Analysis is an agent skill from ginlix-ai/LangAlpha. Competitive landscape analysis: positioning, scorecards, moat assessment, market share trends. Triggers on competitive analysis, competitive landscape, competitor benchmarking, moat assessment, market share, who are the competitors.

Its SKILL.md is about 3.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `references/frameworks.md`, `references/presentation.md` and `references/schemas.md`).

It sits in Marketing & SEO, covering Competitor analysis. The repository describes itself as: Claude Code for Financial Market. The licence is Apache-2.0.

When your agent uses it

  • Competitive analysis
  • Competitive landscape
  • Competitor benchmarking
  • Moat assessment

Example prompts

  • “/competitive-analysis”

Workflow steps

10 steps, taken from the step headings in SKILL.md.

  1. Identify the industry-defining metrics
  2. Market context
  3. Industry economics
  4. Target company profile
  5. Competitor mapping
  6. Positioning visualisation
  7. Competitor deep dives
  8. Comparative analysis
  9. Strategic context
  10. Synthesis

What it can do on your machine

Read from SKILL.md and the folder at commit e05bd91. 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

    No scripts in the folder and no shell commands in SKILL.md.

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

  • Network

    No URLs in SKILL.md.

    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

Competitive Analysis loads about 3.1k tokens when it runs, and up to ~6.3k if it reads all its reference files. Until then it costs about 63 tokens; SKILL.md has 1,676 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~63
When it runs · the whole SKILL.md, loaded when a task matches
~3.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6.3k

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from ginlix-ai/LangAlpha at commit e05bd91, republished under its Apache-2.0 licence (© ginlix-ai). 1,676 words, ~3,131 tokens.

Download SKILL.mdSave it as .claude/skills/competitive-analysis/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
competitive-analysis
description
Competitive landscape analysis: positioning, scorecards, moat assessment, market share trends. Triggers on competitive analysis, competitive landscape, competitor benchmarking, moat assessment, market share, who are the competitors.

Competitive Landscape Mapping

Who competes, on what, and which advantages survive. The product is a comparison, so the comparison has to be real: same period, same metric definition, same basis, with each figure's provenance visible. A table of numbers that were measured differently looks like analysis and is not one.

Evidence labels, source tiers, staleness, the readiness posture and the intake limits: .agents/skills/research-conventions/SKILL.md, read before the first deliverable.

Reference files

  • The deliverable is a deck or a formatted document, or the request specifies titles, chart types or exact figures: .agents/skills/competitive-analysis/references/presentation.md.
  • The set is judged on customer economics rather than units shipped or stores opened: .agents/skills/competitive-analysis/references/unit-economics.md, which carries the benchmark bands (Rule of 40 on EBITDA margin, NDR, LTV:CAC, CAC payback), the cohort matrix and the traps that make two companies look comparable when they are not.
  • Building an M&A transaction table, a scenario table, or a slide skeleton: .agents/skills/competitive-analysis/references/schemas.md.
  • Choosing the two axes for a positioning matrix: .agents/skills/competitive-analysis/references/frameworks.md.

Data standards

These bind every run, whatever the deliverable is.

Provenance on every competitor metric

Each cell in a competitor table carries the figure, its as-of, and one label from the closed set in .agents/skills/research-conventions/references/evidence.md, which also holds the freshness thresholds and the six staleness states. Three of the seven carry most of a competitor table: fact for the company's own filed statements, company claim for a management figure that is not in them (market share, customer count, addressable market), and street estimate for a consensus or single-analyst number, with its vintage and analyst count.

A third-party sizing of a private company is a street estimate: fact is reserved for a primary document or a data-tool figure for a period that has closed. A research house's published sizing carries the house as its estimator and the publication date as its vintage, and anything with no traceable publisher stays needs-source until one is found.

The as-of is the fiscal period for a reported figure, the publication date for an estimate, and the retrieval date for anything built on price. A private-company figure carries a label and an as-of like any other cell, and prints the reader-facing word its label maps to in .agents/skills/research-conventions/references/evidence.md.

When a competitor metric does not exist

Label the gap rather than filling it. The cell reads not disclosed, and the table note says what was searched. Where the missing metric is load-bearing, meaning the ranking or the moat conclusion moves without it, take one of the two exits in the unsupported-claim rule: drop the conclusion that rests on it, or carry a bound ("the range consistent with the reported total is A to B"), label it assumption, and re-read the posture from the ladder in .agents/skills/research-conventions/SKILL.md against the new input state. A plausible-looking estimate with no flag is exactly the failure that rule exists to catch: evidence.md.

Comparability
  • Periods match. Every competitor metric comes from the same fiscal period, and an exception is flagged in the cell: "(FY24)" against "(H1 2024)". Fiscal-period labelling, LTM and NTM windows, one common base date for comparative returns, and margin numerator and denominator pairing: .agents/skills/research-conventions/references/market-data-rules.md.
  • Definitions match. One calculation methodology across the set, stated once where two companies would define the metric differently.
  • Currency normalised. Convert to USD for international sets, and note the rate and the date used.
  • Missing data reads not disclosed per the gap rule in Step 1.
  • Every number cites its source, in the form [Company] [Document] ([Date]).
Source files provided by the user
  • Extract values directly. Use the numbers as they appear rather than recomputing them.
  • Keep one value per metric across every slide and table in the deliverable.
  • Verify anything you are asked to calculate against related figures in the same source.
  • Match the source's precision. Round as it rounds.

Where a source file and a filing disagree, the conflict register in evidence.md decides it and the artifact shows the selection.

Source hierarchy

The general tiers by claim family are in evidence.md and govern. Two additions specific to this work: sell-side research is the usual route to a private competitor's size and is a street estimate with its vintage, and industry research houses are the usual route to a share figure and carry the house and the publication date.

Depth

Default working analysis: 8 to 12 pages, or 12 to 20 slides, plus the comparison workbook. A rapid competitive read is a first pass at up to five slides. Bands and cut order: .agents/skills/research-conventions/references/depth.md.

Workflow phases

Phase 1, scope it. Confirm: single-company deep dive or multi-company comparison; deck or written memo; the specific competitors, dimensions or strategic question in play; whether an investment context needs scenarios and signposts; and which source files exist and which values come out of them.

Phase 2, research, outline, review, build. Run Steps 0 through 9 below, show the outline with the real numbers already in it, and build the final artifact after the outline has been reviewed. That review is an intake exception and yields under .agents/skills/research-conventions/references/intake.md: when this skill runs as an input to another workflow, or the user asked for the finished artifact in one request, present the outline and keep building without waiting on it.

Analysis workflow

Step 0: Identify the industry-defining metrics

Before any pull, name the three to five metrics this industry is actually judged on:

IndustryKey metrics
SaaSARR, NRR, CAC payback, LTV/CAC, Rule of 40 on EBITDA margin
PaymentsGPV, take rate, attach rate, transaction margin
MarketplacesGMV, take rate, buyer/seller ratio, repeat rate
RetailSame-store sales, inventory turns, sales per square foot
LogisticsVolume, cost per unit, on-time delivery, capacity utilisation

For an industry not listed, take the three to five metrics investors and operators use to benchmark it. Use the same set for every company in the comparison.

Step 1: Market context

Market size now and projected, with the source and its vintage. Growth drivers, headwinds, and the trends reshaping the industry.

Correct: "The embedded payments market is $80B to $100B in 2024, growing 20% to 25% a year (research house, 2024)." Not usable: "The market is large and growing rapidly."

Show full SKILL.md (666 more words)Show less
Step 2: Industry economics

Map where the value flows, in the shape the industry actually has:

  • Vertically structured: the value chain layers, with typical margin at each.
  • Platform or network: the participants and the value moving between them.
  • Fragmented: the consolidation dynamic, and how margin differs with scale.
Step 3: Target company profile
MetricValueAs-ofLabel
Revenue$4.96BFY2024fact
Growth+26% y/yFY2024fact
Gross margin45%FY2024fact
Profitability$373M adj. EBITDAFY2024fact
Customers134KQ4 FY2024company claim
Retention92%Q4 FY2024company claim
Market share~15%2024street estimate

For a multi-segment company, add the segment breakdown:

SegmentRevenueRev y/yRev %EBITDAEBITDA y/yMargin
Seg A$25.1B+26%57%$6.5B+31%26%
Seg B$13.8B+31%31%$2.5B+64%18%
Seg C$5.1B-2%12%-$74M-16%-1%
Total$44.0B+18%100%$6.5B15%

Note unallocated corporate costs where the segments do not foot to the total.

Step 4: Competitor mapping

Group the set with whichever cut is real for this industry: by business model (platform, vertical, horizontal), by segment served (enterprise, SMB, consumer), by posture (direct, adjacent, emerging), or by origin (incumbent, disruptor, new entrant).

Step 5: Positioning visualisation
VisualisationBest for
2x2 matrixTwo dominant competitive factors
RadarMulti-factor comparison
Tier diagramNatural clustering into strategic groups
Value chain mapVertical industries
Ecosystem mapPlatform markets
Step 6: Competitor deep dives

Metrics, on the Step 0 set, each row carrying its as-of and label as in Step 3.

Qualitative:

CategoryAssessment
BusinessWhat they do, one sentence
StrengthsTwo or three bullets
WeaknessesTwo or three bullets
StrategyCurrent priorities
Step 7: Comparative analysis
DimensionCompany ACompany BCompany C
Scale●●● $160B●●○ $45B●○○ $8B
Growth●●○ +26%●●● +35%●●○ +22%
Margins●●○ 7.5%●○○ 3.2%●●● 15%

Row-merge discipline. Two competitors share a row only where "Row-merge discipline" in .agents/skills/research-conventions/references/judgment.md allows it.

Step 8: Strategic context

M&A transactions with their multiples and the strategic logic, partnership and integration patterns, capital-raising activity, and regulatory developments.

Step 9: Synthesis

Moat assessment. The rating is a judgement and is written as one: each row shows what was observed, then what we conclude from it.

Moat typeObservedRatingWhy the observation supports it
Network effectsthe flywheel evidence, cross-side or same-sideStrong / Moderate / Weakone clause
Switching costsintegration depth, contractual lock-in, habit
Scale economiesunit cost at volume, minimum efficient scale
Intangible assetsbrand, proprietary data, licences, patents

A Strong with an empty observed column is an opinion in a table. Keep the observation and the rating in separate columns so a reader can disagree with the second while keeping the first. How far the evidence lets the language go: evidence.md.

Then three things: the durable advantages, mapped to the rows above; the structural vulnerabilities that are hard to fix; and the current state against the trajectory, which is where the two diverge.

For an investment context:

ScenarioProbabilityKey driver
Bull30%Share gains, margin expansion
Base50%Current trajectory continues
Bear20%Competitive pressure, margin compression

The probability set follows "Probabilities" in .agents/skills/research-conventions/references/judgment.md, and each scenario names the competitive driver that produces it.

Quality checklist

Verify before delivery. Deck and document formatting has its own checklist in .agents/skills/competitive-analysis/references/presentation.md.

Comparability

  • Every competitor metric is from the same fiscal period, with exceptions flagged in the cell.
  • One metric definition across the whole set.
  • International figures converted at a stated rate and date.

Provenance

  • Every figure carries an as-of and one evidence label.
  • Every number cites its source in [Company] [Document] ([Date]) form.
  • Missing metrics read not disclosed with a table note saying what was searched, and no cell holds an unlabelled estimate.
  • Values taken from user-supplied files match those files exactly, and one metric shows one value everywhere it appears.

Analysis

  • Moat ratings sit beside their observed evidence.
  • Scenario probabilities sum to one, or the weighting is withheld.
  • The comparison table's rows merge only where the hub's row-merge discipline allows.
  • The artifact is inside its depth band and states its readiness posture.

© ginlix-ai, 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

Files

SKILL.md and 4 other files (references) in plugins/langalpha_research/skills/competitive-analysis of ginlix-ai/LangAlpha.

  • SKILL.md
  • references/frameworks.md
  • references/presentation.md
  • references/schemas.md
  • references/unit-economics.md

Open the folder on GitHubat commit e05bd91

Compare with similar skills

Competitive 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.

Competitive Analysis compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Competitive Analysis this skillginlix-ai/LangAlpha1.8k—~3.1kAutomated safety check: PassApache-2.0
SEO Content Brief GeneratorAgriciDaniel/claude-seo19k2 repos~2.6kAutomated safety check: PassMIT
SEO DataforseoAgriciDaniel/codex-seo7972 repos~4.6kAutomated safety check: PassMIT
Competitor ProfilingNexus-JPF/note-companion8704 repos~3.5kAutomated safety check: PassMIT
Startup Competitorsferdinandobons/startup-skill1.2k—~4.1kAutomated safety check: PassMIT
Amazon Listing Competitor Analysisbrowser-act/skills6.1k1 repos~3.2kAutomated safety check: PassMIT

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Categories

Questions about Competitive Analysis

What does Competitive Analysis do?

Competitive landscape analysis: positioning, scorecards, moat assessment, market share trends. Competitive Analysis is an agent skill from ginlix-ai/LangAlpha. Competitive landscape analysis: positioning, scorecards, moat assessment, market share trends.

When should I use Competitive Analysis?

Competitive Analysis fits situations like: competitive analysis; competitive landscape; competitor benchmarking; moat assessment.

How do I install Competitive Analysis in Claude Code?

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

How do I install Competitive Analysis in Codex?

Run `npx skills add ginlix-ai/LangAlpha --skill competitive-analysis -a codex`. Or copy the skill folder (plugins/langalpha_research/skills/competitive-analysis in ginlix-ai/LangAlpha) into .agents/skills/competitive-analysis in your project. Codex loads it when a task matches its description.

Can I use Competitive 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 ginlix-ai/LangAlpha --skill competitive-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/competitive-analysis, .gemini/skills/competitive-analysis, .github/skills/competitive-analysis and .opencode/skills/competitive-analysis in your project.

What does Competitive Analysis need to run?

SKILL.md names no scripts, command-line tools or credentials: Competitive Analysis is instructions for the agent only.

Does Competitive Analysis access the network?

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.

Is Competitive 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. Review the folder before installing.

What licence does Competitive Analysis use?

Competitive Analysis 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.

How many tokens does Competitive Analysis use?

About 3.1k tokens (SKILL.md is roughly 13k 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 3.2k tokens, read only when the agent opens those files.

What are the alternatives to Competitive Analysis?

Skills that share tags, products or a category with Competitive Analysis: SEO Content Brief Generator (AgriciDaniel/claude-seo, 19k stars), SEO Dataforseo (AgriciDaniel/codex-seo, 797 stars), Competitor Profiling (Nexus-JPF/note-companion, 870 stars) and Startup Competitors (ferdinandobons/startup-skill, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Competitive Analysis?

ginlix-ai (a GitHub organization) maintains it in ginlix-ai/LangAlpha, which has 1,811 GitHub stars. The repository holds 37 skills in this directory. The repository was last updated on October 9, 2026.

Source: ginlix-ai/LangAlpha on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.