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Competitor Profiling

Community
mia-ppp
competitor-profiling

Use when the user wants competitor research, a named competitor profile or dossier, competitive landscape discovery, an alternative-universe comparison, or competitive signals/change investigation. Accept URLs, supplied research, and targeted verification requests. For external market/category conditions, see market-intelligence; for comparison pages, see competitor-alternatives; for battlecards, see sales-enablement; for closed-deal causes, see win-loss-intelligence.

Overview

Publishermia-ppp
RepositoryPMM-Skills
Skill namecompetitor-profiling
Stars
76
Forks
2
Bundled files
4
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.

  • 4 bundled files

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

  • Open source

    Published by mia-ppp on GitHub. Read the source before you install it.

Installation

Install the Competitor Profiling 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.
    https://github.com/mia-ppp/PMM-Skills/tree/main/skills/competitor-profiling
  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/mia-ppp/PMM-Skills.git /tmp/PMM-Skills
mkdir -p .claude/skills
cp -r /tmp/PMM-Skills/skills/competitor-profiling .claude/skills/competitor-profiling
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Competitor Profiling 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 Competitor Profiling 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 Competitor Profiling 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.

Competitor Profiling

Establish sourced facts about alternatives, structure a comparable landscape, and verify changes against dated baselines. Separate facts, reported claims, interpretations, and implications. Research does not approve strategy.

Before starting

  • Resolve the active project/product scope. Keep other projects' evidence and approval references out of this return; IDs are project-scoped.
  • Read ../_shared/evidence-gaps.md and ../_shared/ssot-consumption.md.
  • Read ../_shared/context-establishment.md when available. It owns Phase 1 evidence, readiness, and handoff/return semantics. Otherwise use the compatible minimum in references/templates.md. Read that reference for domain checks and the return template on every run.
  • Load relevant manifest-mapped approved context. Record version, authority, health, and gaps. Bootstrap context stays provisional.
  • Preserve originating HND/GAP/SRC/FND IDs, exact question, completion criteria, scope, constraints, opposing evidence, and return destination.
  • Inventory profiles, raw captures, supplied dossiers, customer findings, and dated snapshots before collecting more. Mark inspection coverage and unavailable material.
  • Resolve job/problem or named entity, geography, period, intended use, and depth. Ask only for missing facts that materially change the work. Exploration requires useful scope, not approved personas or an accepted market.

Choose the smallest useful mode

Read the selected section of references/modes.md. Use only modes needed for the question.

ModeExact job and triggersOutput
Competitive landscapeIdentify and structure the relevant alternative universe. “Who competes for this job?” “Map our alternatives.”Inclusion rationale, alternative register, supported comparison, coverage/freshness view.
Entity profilingEstablish sourced facts about a named alternative. “Profile this competitor.” “Verify whether this feature exists.”Focused or full dossier with field-level provenance and verification.
Competitive signalsIdentify and verify changes against a dated baseline. “What changed since our last profile?” “Investigate this launch.”Event/delta register with verification, materiality, and affected references.

Landscape discovery may commission focused profiles before comparison. Signals refresh affected fields and comparisons without repeating full studies. Named-entity requests need not start with landscape discovery.

Research and evidence

Use existing evidence and the smallest useful verification. URLs are optional. Methods include supplied-material analysis, documentation, published commercial terms, release notes, original filings, permitted demos/trials, and customer findings. Scraping and SEO are optional methods, not prerequisites. Read references/tool-reference.md only when those tools fit the question. Missing tools never justify invented data.

Keep these distinctions explicit:

  • Competitor-authored claim versus documented behavior versus direct verification.
  • Customer-reported experience versus general product fact.
  • Unknown capability versus scoped evidence of absence in a tier/version.
  • Announcement versus available, beta, limited access, or withdrawn capability.
  • Observed change versus inference about intent, demand, or commercial impact.
  • Search overlap versus evidence of commercial competition.

Record lineage and counterevidence. Copies of one announcement are one signal. Ratings, traffic, and review counts do not verify revenue or customer totals. Never infer absence from an omitted feature or inaccessible page. Compare equivalent versions, tiers, currencies, billing periods, and regions. No universal source-count threshold establishes confidence or readiness.

Persistence and refresh

Preserve the existing project-relative competitor-profiles location when used:

text
competitor-profiles/
  raw/<alternative-slug>/<YYYY-MM-DD>/<capture-id>/
    scrapes/
    seo/
    reviews/
    supplied/
  <alternative-slug>.md
  _summary.md
  _signals.md

Use only applicable subdirectories. Existing date-only raw folders remain valid. A capture ID prevents overwriting same-day runs. Retain source IDs and precise paths on refresh. Capture collected raw evidence before synthesis when saving is part of the task. Reference supplied originals without rewriting them; respect access/use restrictions. If capture is unavailable, disclose the limitation. Never overwrite earlier raw captures. Preserve profile versions, change history, and supersession links. _summary.md is a derived comparison, not another authority. _signals.md is an optional noncanonical event view, not an installed monitor.

Save only in the user's project when requested or workflow-authorized. Do not write into the skills repository during production runs. Research or a cadence does not authorize outreach, account creation, spending, installed monitoring, or sending alerts.

Ownership and handoffs

NeedOwner and boundary
Market conditions, category conventions, opportunity hypothesesmarket-intelligence. Competitive gaps do not establish demand.
Customer experience themes and reusable languagecustomer-research. Reuse findings and attribute reported experience.
Closed-deal causes and buyer/seller disagreementwin-loss-intelligence. Competitor presence is not loss causality.
Objection libraryobjection-intelligence. Route evidence, not invented responses.
Where/whether to enter and company-specific sizingmarket-entry-brief. Landscape relevance does not select a market.
Who to target and buying groupicp-and-buyer-personas. Their targeting claims do not select our ICP.
Our positioning, differentiation, and category/framepositioning-strategy. Maps/whitespace are research, not strategic choices.
Messaging architecturemessaging-framework. Observed wording does not change our messages.
Pricing/packaging decisionspricing-strategy. Record terms without recommending our price.
GTM or competitive response decisionsgo-to-market-strategy and relevant decision owners. Surface review needs without committing actions.
Battlecards and comparison pagessales-enablement and competitor-alternatives. Consume sourced views and approved company claims.
Integrated context and goal-relative readinessproduct-marketing-context. Return findings without becoming an orchestrator.
Approved canon, drift verdicts, and persistencessot-context-loop. Explicit human approval is mandatory for canonical changes.

Never write canonical files, decisions, manifests, or state.md. Return to originating PMC or named requester using the packet in templates.md. Suggest competitive context for living/06-competitive.md and supporting evidence for living/07-evidence.md without duplicating claims. SSOT chooses destinations and gates. Verified external changes are not SSOT drift verdicts and never silently rewrite strategy or collateral.

Output rules

  • Open with Inputs and assumptions, selected mode, scope, and inspected coverage.
  • Use Sourced / Assumed / Gap with kind, verification, confidence/rationale, limitations, approval status, and review trigger.
  • Expose derivations and labeled inputs without adding a Derived evidence tag.
  • Preserve unknowns, opposing evidence, and completion-criteria assessment.
  • End with ranked Evidence gaps: top five in the body, all others in an appendix. Give owners and milestones, explicitly marking suggestions.
  • Use no em dashes. Keep sentences short and bullets led by outcomes.

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 Competitor Profiling AI skill do?

Use when the user wants competitor research, a named competitor profile or dossier, competitive landscape discovery, an alternative-universe comparison, or competitive signals/change investigation. Accept URLs, supplied research, and targeted verification requests. For external market/category conditions, see market-intelligence; for comparison pages, see competitor-alternatives; for battlecards, see sales-enablement; for closed-deal causes, see win-loss-intelligence.

Why use Competitor Profiling on TypingMind?

Because you install it once and use it with any model. Competitor Profiling 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 Competitor Profiling in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mia-ppp/PMM-Skills/tree/main/skills/competitor-profiling. 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 Competitor Profiling?

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 Competitor Profiling?

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

Is the Competitor Profiling AI skill free?

Yes. It is published on GitHub by mia-ppp 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.

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