product-analyst

product-analyst is a skill for Claude Code, Codex from jggomez/expert-ai-developer-skills. It costs 65 tokens per session (1,252 once invoked), scanned A, original, Apache-2.0.

Analyzes ambiguous feature requests, clarifies business rules, and authors the ultra-concise ## Product section of the single discovery file docs/ /spec.md (<= 50 lines) with standard User Stories (US-XX) and testable Acceptance Criteria (AC-XX).

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions Claude Code.

Install with agentmods
npx agentmods add skills/jggomez/expert-ai-developer-skills/product-analyst
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 jggomez/expert-ai-developer-skills --skill product-analyst
Clone the repo
git clone --depth 1 https://github.com/jggomez/expert-ai-developer-skills

Made for: Claude Code, Codex.

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 product-analyst

README.md
[![agentmods](https://agentmods.dev/badge/skills/jggomez/expert-ai-developer-skills/product-analyst/github.svg)](https://agentmods.dev/skills/jggomez/expert-ai-developer-skills/product-analyst)
Your own site
<a href="https://agentmods.dev/skills/jggomez/expert-ai-developer-skills/product-analyst"><img src="https://agentmods.dev/badge/skills/jggomez/expert-ai-developer-skills/product-analyst/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 product-analyst

Your own site · 80×15
<a href="https://agentmods.dev/skills/jggomez/expert-ai-developer-skills/product-analyst"><img src="https://agentmods.dev/badge/skills/jggomez/expert-ai-developer-skills/product-analyst.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 65 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,252 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 $0.00065 $0.01252
Opus 5.5 $0.00026 $0.00501
Sonnet 5.5 $0.00013 $0.00250
Haiku 4.5 $0.00006 $0.00125

Measured today against content hash ef776caf672a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

product-analyst 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 today.

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/antigravity/python-backend/skills/product-analyst/SKILL.md · 56 lines

How it starts

The opening of the file, as written. The whole thing — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Product Analyst Skill

Overview

This skill converts underspecified feature requests into crisp, directly testable product specifications stored in the ## Product section of the single discovery file docs/<feature-name>/spec.md (section strictly capped at <= 50 lines, zero filler prose). The section follows a fixed 4-part standard (Objective, Scope, User Stories, Acceptance Criteria & Edge Cases) so engineering and QA have exact US-XX -> AC-XX traceability.

When to Use

Capability-Gated Trigger Rules

  • INVOKE ONLY IF business scope, user stories, or acceptance criteria are ambiguous or missing.
  • SKIP when the user prompt already defines clear scope/stories, or for bugfixes, refactors, chores, documentation updates, and purely technical CLIs.
  • Delegate Elsewhere: System schemas & ADRs -> senior-architect-engineering; UI tokens & screens -> ui-ux-designer; TDD coding -> code-implementer.

Process

Phase 1: Context Check & Targeted Clarification

  1. Inspect existing routes, models, and docs/ (docs/specifications/ if present) to avoid asking questions already answered by the codebase.
  2. If business rules or boundaries remain genuinely ambiguous, ask concise option-based questions with clear trade-offs (never vague open-ended prompts).

Phase 2: Author the ## Product Section (docs/<feature-name>/spec.md, <= 50 lines)

If docs/<feature-name>/spec.md is missing, create it from the 3-heading template (# Spec: <feature-name>, ## Product, ## Design, ## Architecture). Edit ONLY ## Product (<= 50 lines hard cap; ## Design / ## Architecture belong to other specialists) using the exact 4-part template in references/prd-template.md:

  1. ### Objective: 2–4 lines stating the concrete problem and measurable business outcome.
  2. ### Scope: Crisp In-Scope and Out-of-Scope bullets preventing scope creep. For UI, add a Data sources bullet: each screen's data, its real source, and whether it exists.
  3. ### User Stories: Numbered US-01, US-02 in strict standard format:
    • As a <role>, I want <action>, so that <outcome> (or Como <rol>, quiero <acción>, para <beneficio>).
  4. ### Acceptance Criteria & Edge Cases: Numbered AC-01, AC-02 explicitly mapped to US-XX (AC-01 (US-01)), written as directly testable Given/When/Then or crisp bullets covering validation, permissions, and boundary/failure cases.

Read the full file on GitHub · 56 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. today First seen · 56 lines · 65 tokens per session scan A ef776caf672a

Subscribe to this mod's changes

product-analyst is a skill published in the GitHub repository jggomez/expert-ai-developer-skills (30 stars, last pushed yesterday), licensed Apache-2.0. It adds 65 tokens to every session and 1,252 once invoked, about $0.0003 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 2026-11-06.

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