research-positioning

research-positioning is a skill for Claude Code, Codex from forsvn-labs/meta-skills. It costs 59 tokens per session (603 once invoked), scanned A, original, MIT.

A research process for deciding who a product should serve, what alternatives customers have, and how the product should be described in the market. Positioning is the clear explanation of why a product fits a particular customer and situation.

In plain words
What is it for?
Use it to research ideal customers, competitors and substitutes, market segments, customer language, product categories, offers, and the message that should guide marketing.
Why use it?
It separates observed facts from conclusions and temporary assumptions, so messaging is based on evidence rather than guesswork. It also focuses research on a decision instead of collecting facts without a use.

Skill for Claude CodeCodex

Written for Claude Code and Codex: shipped in a Claude Code plugin, but also agents/openai.yaml present.

Part of the conquistador plugin — 21 skills shipped together

Good fit Use it to research ideal customers, competitors and substitutes, market segments, customer language, product categories, offers, and the message that should guide marketing.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/forsvn-labs/meta-skills/research-positioning
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 forsvn-labs/meta-skills --skill research-positioning
Clone the repo
git clone --depth 1 https://github.com/forsvn-labs/meta-skills

Made for: Claude Code, Codex.

Or install conquistador, the plugin that ships this one along with the rest of its 21 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 research-positioning

README.md
[![agentmods](https://agentmods.dev/badge/skills/forsvn-labs/meta-skills/research-positioning/github.svg)](https://agentmods.dev/skills/forsvn-labs/meta-skills/research-positioning)
Your own site
<a href="https://agentmods.dev/skills/forsvn-labs/meta-skills/research-positioning"><img src="https://agentmods.dev/badge/skills/forsvn-labs/meta-skills/research-positioning/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 research-positioning

Your own site · 80×15
<a href="https://agentmods.dev/skills/forsvn-labs/meta-skills/research-positioning"><img src="https://agentmods.dev/badge/skills/forsvn-labs/meta-skills/research-positioning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 59 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 603 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.
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 $0.00059 $0.00603
Opus 5 $0.00030 $0.00302
Sonnet 5 $0.00012 $0.00121
Haiku 4.5 $0.00006 $0.00060

Measured 12d ago against content hash 48c72a5fbf0a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

research-positioning 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 12d 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/research-positioning/SKILL.md · 74 lines

How it starts

The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Research and position a product

Turn incomplete product context and current evidence into a decision-ready market position.

Establish the decision

Name the decision this research must change. Use available project context before asking anything. Ask at most one bundled question when different answers would materially change the conclusion.

Build the minimum useful model:

  • Product: mechanism, maturity, price, constraints, and demonstrated capabilities.
  • Audience: buyer, user, situation, decision power, and switching trigger.
  • Costly moment: the event that makes the problem urgent or expensive.
  • Alternatives: direct products, adjacent substitutes, agencies, spreadsheets, and doing nothing.
  • Change: the credible before-and-after outcome.
  • Proof: product evidence, customer behavior, demonstrations, or defensible reasoning.

Research with evidence discipline

Use current primary sources for volatile market, competitor, pricing, and platform claims. Separate:

  • Observed: directly present in product, analytics, customer language, or a cited source.
  • Inferred: the best explanation supported by observations.
  • Assumed: necessary to continue but not yet supported.

Treat multiple comments from one thread as one selection mechanism. Name sample bias and how sources were recruited. Keep single-source observations as hypotheses. Prefer customer behavior and language over demographic stereotypes. Describe audience habitats with named communities and observed behavior, not a generic platform list.

For market size, state whether the estimate is top-down or bottom-up and show the governing inputs. Do not manufacture precision.

Make the positioning decisions

Resolve:

  1. the narrowest valuable audience to serve now;
  2. the costly moment that creates urgency;
  3. the real alternative used today;
  4. the distinct product mechanism;
  5. the strongest credible promise;
  6. the proof that reduces the main objection;
  7. the category or frame that makes the choice legible.

Read the full file on GitHub · 74 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 12d ago First seen · 74 lines · 59 tokens per session scan A 48c72a5fbf0a

Subscribe to this mod's changes

research-positioning is a skill published in the GitHub repository forsvn-labs/meta-skills (14 stars, last pushed 1mo ago), licensed MIT. It adds 59 tokens to every session and 603 once invoked, about $0.0003 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.

Related

Other skills, from other repositories

data-charts-tako

Search and visualize the world's data - get charts, insights, and embeddable knowledge cards for finance, economics, demographics, sports, and more.

gooseworks-ai/goose-skills · 35 tokens

apollo-lead-finder

Two-phase Apollo.io prospecting: free People Search to discover ICP-matching leads, then selective enrichment to reveal emails/phones (credits per contact). Creates Apollo lists. Deduplicates against existing contacts by LinkedIn URL.

gooseworks-ai/goose-skills · 51 tokens

monorepo-management

Master monorepo management with Turborepo, Nx, and pnpm workspaces to build efficient, scalable multi-package repositories with optimized builds and dependency management. Use when setting up monorepos, optimizing builds, or managing shared dependencies.

wshobson/agents · 54 tokens

browse-and-evaluate

Use when exploring the ai-agent-skills catalog to find, compare, and evaluate skills before installing. Always use --fields to limit output size and --dry-run before committing to an install.

MoizIbnYousaf/Ai-Agent-Skills · 43 tokens

render-airdrop-carousel

Assemble a viral iOS "AirDrop" notification-carousel video ad (≈6–8s, 9:16) from a brand line plus 6–16 real product photos — a native AirDrop share-sheet card ("Brand would like to share a · Decline / Accept") springs up and its preview window CYCLES through the products, landing on a range/lineup payoff with an…

gooseworks-ai/goose-skills · 207 tokens

render-3d-product-showcase

Assemble a premium 3D product-showcase ad from a config — four beat clips (an orbiting hero rotation, a macro push-in, a physics reveal, a typographic close) normalized to the brand-color canvas, hard-concatenated in order, closed on a deterministic Playwright brand end card, and mixed under one instrumental bed at…

gooseworks-ai/goose-skills · 159 tokens