competitor-discovery

competitor-discovery is a skill for Claude Code from anysiteio/agent-skills. It costs 209 tokens per session (7,177 once invoked), scanned A, original, MIT.

A research guide for mapping the alternatives customers might compare with a startup, including competing products, substitutes, free tools, and doing nothing.

In plain words
What is it for?
Use it to build or check a competitor slide, understand a product’s choice landscape, and identify alternatives customers may consider.
Why use it?
It helps reveal the choices that matter in real buying decisions instead of relying only on competitors named in a pitch deck.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: positional $N argument.

Part of the anysite-skills plugin — 33 skills shipped together

Good fit Use it to build or check a competitor slide, understand a product’s choice landscape, and identify alternatives customers may consider.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/anysiteio/agent-skills/competitor-discovery
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add anysiteio/agent-skills --skill competitor-discovery
Clone the repo
git clone --depth 1 https://github.com/anysiteio/agent-skills

Made for: Claude Code.

Or install anysite-skills, the plugin that ships this one along with the rest of its 33 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for competitor-discovery

README.md
[![agentmods](https://agentmods.dev/badge/skills/anysiteio/agent-skills/competitor-discovery/github.svg)](https://agentmods.dev/skills/anysiteio/agent-skills/competitor-discovery)
Your own site
<a href="https://agentmods.dev/skills/anysiteio/agent-skills/competitor-discovery"><img src="https://agentmods.dev/badge/skills/anysiteio/agent-skills/competitor-discovery/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for competitor-discovery

Your own site · 80×15
<a href="https://agentmods.dev/skills/anysiteio/agent-skills/competitor-discovery"><img src="https://agentmods.dev/badge/skills/anysiteio/agent-skills/competitor-discovery.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 209 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 7,177 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Excessive Agency · line 263
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00209 $0.07177
Opus 5 $0.00105 $0.03589
Sonnet 5 $0.00042 $0.01435
Haiku 4.5 $0.00021 $0.00718

Measured 10d ago against content hash a63417806fab, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

competitor-discovery scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/competitor-discovery/SKILL.md · 351 lines

How it starts

The opening of the file, as written. The whole thing — 351 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Competitor Discovery

The pitch deck usually names 2–3 lookalikes. The real comparison set is whatever the customer almost picked instead — including substitutes, free generic tools, "doing nothing," and adjacent-market players one feature-pivot away. This skill produces that map.

Framing (so the categories don't drift)

Three industry frameworks converge on what to capture:

  • Christensen JTBD: The customer is "hiring" your product for a job. The true competitor is anything else they could hire for the same job — including bananas (vs. milkshakes), spreadsheets (vs. SaaS), boredom (vs. Facebook).
  • April Dunford (Obviously Awesome): Competitive alternatives are the starting point of positioning. Ask "what would the customer do if our product didn't exist?" — this surfaces "do nothing" as the #1 alternative in ~25% of lost enterprise deals. Beware "phantom competitors" — theoretical companies that never show up in real deals; they dilute positioning.
  • Porter's Five Forces — Substitutes + New Entrants: Substitutes solve the same outcome with a different category. New entrants are adjacent-market players one feature pivot away.

These map to our four output categories (Direct / Substitute / Workaround / Convergence). Detectors, app stores, compliance tools, payment processors, distribution platforms — these are "rule-setters" that shape the market, not competitors. Note them in context.

When this skill applies

  • A founder names 1–3 obvious competitors; you validate or expand
  • Pre-flight before customer-pain-mining or positioning-map
  • Mapping a product into a category when the category is fuzzy
  • Sanity-checking a pitch deck competitor slide

What you need

  1. Product name (e.g. "Anysite")
  2. One-liner — what it does, for whom (e.g. "AI writing for college students that drafts, cites, runs integrity checks")
  3. Pitch-deck competitors if named (optional)
  4. Segment indicator — consumer / SMB / B2B / DevTool / DeepTech. This determines which source order to use.
  5. Modetop5 (default; produces 5 anchor names + 1 workaround) or landscape (produces 5 anchors + 25-70 name long-tail + 2 suggested strategic-group axes for positioning-map).

Read the full file on GitHub · 351 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 10d ago First seen · 351 lines · 0 tokens per session scan A a63417806fab

Subscribe to this mod's changes

competitor-discovery is a skill published in the GitHub repository anysiteio/agent-skills (19 stars, last pushed 25d ago), licensed MIT. It adds 209 tokens to every session and 7,177 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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