pm-competitive

pm-competitive is a skill for Claude Code, Codex from VandanaAjayDubey111/great-pm. It costs 35 tokens per session (959 once invoked), scanned A, original, MIT.

A competitor-analysis workflow that examines one competitor or a whole market around a customer job. A customer job is the task or problem people are trying to solve.

In plain words
What is it for?
Use it to compare competitors, study a market landscape, and identify ways a product could be positioned differently.
Why use it?
It replaces an informal competitor review with a structured brief that highlights gaps in market positioning.

Skill for Claude CodeCodex

Written for Claude Code and Codex: $ARGUMENTS substitution, but also agents/openai.yaml present. Also seen: mentions Codex; $skill-name invocation.

Part of the great-pm plugin — 114 skills, 34 commands, 48 agents, 5 hooks shipped together

Good fit Use it to compare competitors, study a market landscape, and identify ways a product could be positioned differently.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/vandanaajaydubey111/great-pm/pm-competitive
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 VandanaAjayDubey111/great-pm --skill pm-competitive
Clone the repo
git clone --depth 1 https://github.com/VandanaAjayDubey111/great-pm

Made for: Claude Code, Codex.

Or install great-pm, the plugin that ships this one along with the rest of its 114 skills, 34 commands, 48 agents, 5 hooks.

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 pm-competitive

README.md
[![agentmods](https://agentmods.dev/badge/skills/vandanaajaydubey111/great-pm/pm-competitive/github.svg)](https://agentmods.dev/skills/vandanaajaydubey111/great-pm/pm-competitive)
Your own site
<a href="https://agentmods.dev/skills/vandanaajaydubey111/great-pm/pm-competitive"><img src="https://agentmods.dev/badge/skills/vandanaajaydubey111/great-pm/pm-competitive/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 pm-competitive

Your own site · 80×15
<a href="https://agentmods.dev/skills/vandanaajaydubey111/great-pm/pm-competitive"><img src="https://agentmods.dev/badge/skills/vandanaajaydubey111/great-pm/pm-competitive.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 35 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 959 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 $0.00035 $0.00959
Opus 5.5 $0.00014 $0.00384
Sonnet 5.5 $0.00007 $0.00192
Haiku 4.5 $0.00003 $0.00096

Measured 1mo ago against content hash 8b16c459c204, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

pm-competitive 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 1mo 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.

plugins/great-pm/skills/pm-competitive/SKILL.md · 86 lines

How it starts

The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Codex host binding

  • Treat references to Claude slash workflows as the equivalently named Codex skill.
  • Before delegating to any specialist, read the great-pm-runtime skill and the selected packaged role file.
  • Treat "invoke", "assign", "delegate", "spawn", and source Agent-tool instructions as a required Codex spawn_agent call with that role and a bounded assignment.
  • For the spawn tool's task_name or agent_name identifier, replace canonical role-name hyphens with underscores (query-refiner-pm → query_refiner_pm). Keep canonical names unchanged in prompts, filenames, verdict logs, and user-facing output; this is an internal identifier mapping, not a role rename.
  • Store every returned agent identifier. Never call a wait tool until a spawn has returned an identifier, and wait only on identifiers returned by successful spawns.
  • If spawn_agent is unavailable or a spawn fails, report BLOCKED; do not impersonate the specialist or wait on an empty agent set.
  • Resolve bundled paths from the installed GreatPM plugin root.
  • Ignore Claude-only model aliases, colors, turn limits, and tool allowlists.
  • Preserve GreatPM human gates, governance, state, and reporting contracts.

You are the great-pm $pm-competitive command. Build a competitive view.

Parse arguments

  • <competitor-name | jtbd-slug> (required) → either a single competitor or a JTBD slug (in which case the agent enumerates the landscape).
  • --depth= (default: quick).
    • quick — public surface (site, docs, pricing page, recent announcements).
    • deep — quick + user reviews + g2/capterra + estimated funnel + inferred metric movements.

Pre-flight

TARGET="${1:?usage: $pm-competitive <competitor-or-jtbd> [--depth=...]}"
mkdir -p .great-pm/drafts

Operating procedure

  1. Step 0 — refine the user's query (transparent Mode B). Invoke query-refiner-pm with $ARGUMENTS. The refiner returns:
    You typed:  <original>
    
    Refined to: <refined brief>
    
    What changed: <one line>
    
    Proceeding with refined. Reply "use original" to override.
    
    Use the refined version as the brief for subsequent steps UNLESS the user replies "use original". Log the refinement to .great-pm/refinements/$(date +%Y-%m-%d).log. This wiring is universal across great-pm commands per the gate-policy: explicit discipline — you make the user's leverage visible while preserving their ability to override.

Read the full file on GitHub · 86 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. 1mo ago First seen · 86 lines · 35 tokens per session scan A 8b16c459c204

Subscribe to this mod's changes

pm-competitive is a skill published in the GitHub repository VandanaAjayDubey111/great-pm (3 stars, last pushed 1mo ago), licensed MIT. It adds 35 tokens to every session and 959 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-21.