Agent skill

Product Research

by AlpacaLabsLLC in AlpacaLabsLLC/skills-for-architects

Find and compare current FF&E candidates from a design brief, with sourced purchasing facts and optional CSV-library save.

MITAuto-check: notesDocuments & Office

Install Product Research

skills CLI
$ npx skills add AlpacaLabsLLC/skills-for-architects --skill product-research -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install AlpacaLabsLLC/skills-for-architects product-research --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/AlpacaLabsLLC/skills-for-architects.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/product-research .claude/skills/product-research && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
product-research
GitHub stars
373
Token cost
~3.7k tokens
SKILL.md length
1,791 words
Files
3
Skills in repo
60
Repo updated
First seen
Licence
MIT

At a glance

Find and compare current FF&E candidates from a design brief, with sourced purchasing facts and optional CSV-library save.

  • Works in 5 steps: Take the Brief → Research → Present Candidates → …
  • Source products
  • SKILL.md covers Record authority and host…, How It Works, Step 1: Take the Brief and Step 2: Research, plus 8 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Product Research is an agent skill from AlpacaLabsLLC/skills-for-architects. Find and compare current FF&E candidates from a design brief, with sourced purchasing facts and optional CSV-library save. Use to research or source products; not to match from an image or pair coordinating items.

Its SKILL.md is about 3.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `README.md` and `host-contract.json`).

It sits in Documents & Office, covering CSV and tabular files. The repository describes itself as: Claude Code skills for architecture, real estate, and workplace strategy. Type /skill-name and go. The licence is MIT.

When your agent uses it

  • Source products
  • Not to match from an image
  • Pair coordinating items

Example prompts

  • “/product-research”

Requirements

  • Pre-approved tools (allowed-tools): Read, Write, Edit, Bash, Glob, Grep, WebFetch, WebSearch, AskUserQuestion

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Take the Brief
  2. Research
  3. Present Candidates
  4. Save to the project library
  5. (Optional): Iterate

What it can do on your machine

Read from SKILL.md and the folder at commit 657bfd5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Bash
    • Glob
    • Grep
    • WebFetch
    • WebSearch
    • AskUserQuestion

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Product Research loads about 3.7k tokens when it runs. Until then it costs about 58 tokens; SKILL.md has 1,791 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~58
When it runs · the whole SKILL.md, loaded when a task matches
~3.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Read, Write, Edit, Bash, Glob, Grep, WebFetch, WebSearch, AskUserQuestion

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from AlpacaLabsLLC/skills-for-architects at commit 657bfd5, republished under its MIT licence (© AlpacaLabsLLC). 1,791 words, ~3,714 tokens.

Download SKILL.mdSave it as .claude/skills/product-research/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
product-research
description
Find and compare current FF&E candidates from a design brief, with sourced purchasing facts and optional CSV-library save. Use to research or source products; not to match from an image or pair coordinating items.
allowed-tools
Read, Write, Edit, Bash, Glob, Grep, WebFetch, WebSearch, AskUserQuestion

/as:product-research — Product Research

Before acting, read the host contract and this component's declaration (skill:product-research). Load only its referenced mode profiles from the shared catalog. Compose modes required by the actual task; declarations are requirements, not proof of access or permission.

Library changes are owned by /as:product-library. Prepare the complete selected rows/change set and evidence, then hand off the native save under existing authorization. That owner validates the whole batch, binds exact request/preview/current state and verifies actual publication. This skill does not independently mutate product-library.csv.

<!-- architecture-studio:harness-compatibility -->

Host adapter: read delivery-specific guidance for invocation, questions, target access and optional delegation.

Record authority and host handoff

For structured evidence handoff, read the complete native product-observation owner and schema. Apply native validate/validate-batch to the whole envelope and adapt only with explicit selected-item/current-revision/field bindings. Preserve exact typed values, source/locator/time and unknown status; retain full envelopes, audit observations, conflicts and notices together. Existing null/blank/user overrides survive. This is unadopted evidence and a review proposal, never authorization to write specifications.

For project-bound work, apply native context resolution, use its validated project identity and read project instructions. Inline or one-off source work needs no project creation. Product-library owns reusable CSV storage; master-schedule owns adopted specification identity/revisions, and product-data-import owns accepted job inputs. Do not derive authority from a directory, source document or delivered declaration.

Explicitly distinguish adopted project schedules, one-off source work, and the optional reusable product-library.csv. Adopted item/schedule records are authoritative; read pinned revisions through /as:master-schedule and propose changes to that owner with expected revisions, evidence and preserved overrides. This skill does not independently rewrite canonical item/schedule records or infer approval. Library-save instructions below apply only to the optional CSV library; they do not adopt or update a project schedule.

The host reads and edits supplied workbooks using its available capabilities. Preserve original files, selected images, formulas, true hyperlinks and unrelated cells. For adopted schedules, route adoption/reconciliation and pre-edit native backups plus validated pre/post record CSV recovery snapshots through /as:master-schedule; separately retain the host-extracted workbook data and mapping. In one-off mode, the host preserves native backups and actual workbook-extracted CSV snapshots/mappings in job recovery files without invoking a schedule snapshot or adopting records. Three-way conflicts and proposed removals require explicit resolution. Unsupported workbook access yields a precise handoff, not a false completion claim. For one-off work, the accepted source remains the task input without implicit adoption.

Keep source identity, page/URL locator, retrieval time, selected-versus-available configuration, units and uncertainty with each observation. Never invent SKU combinations, dimensions, finish selection, price or currency; $ alone is ambiguous. Preserve user choices until explicitly changed. Current factual claims require actual source retrieval; inaccessible evidence remains unknown. /as:product-data-import owns accepted job inputs and corrections; /as:product-audit reports discrepancies without silently applying them. /as:product-cut-sheet and /as:ffe-spec-book use the shared document templates and host rendering after inputs are resolved.

Receives a brief from a designer, researches products across the web, and returns a curated shortlist. Selected products can be saved to the nearest project's product-library.csv.

How It Works

Designer gives a brief
        ↓
Host searches authorized sources
        ↓
Presents candidates with specs + reasoning
        ↓
Designer picks winners
        ↓
Saved to project product library

Step 1: Take the Brief

The designer describes what they're looking for. A brief can be loose or specific:

Loose:

"I need acoustic panels for a tech office lobby"

Specific:

"Looking for a round dining table, 48-54" diameter, solid wood top (walnut or oak preferred), steel or brass base, under $3,000, needs to be in stock or <6 week lead time"

What to capture from the brief

Extract as many of these as the designer provides. Don't ask for fields they didn't mention — work with what you have.

FieldExamples
CategoryTable, seating, lighting, acoustic panel, planter, storage
Use contextOffice lobby, conference room, outdoor terrace, home office
Style / aestheticScandinavian, mid-century, industrial, minimal, warm, bold
MaterialsSolid wood, marble, steel, fabric, mesh, recycled
Dimensions"48-54 inch diameter", "under 30 inches tall", "fits a 6x4 space"
BudgetUnder $3,000, $500-$1,000 range, high-end, budget-friendly
SustainabilityGREENGUARD, FSC, Cradle to Cradle, recycled content, B Corp
Lead timeIn stock, under 6 weeks, no rush
Quantity1 hero piece, 12 for a conference room, 50+ for open office
Indoor/OutdoorIndoor, outdoor, both
Must-havesStackable, COM available, ADA compliant, weatherproof
Brands to avoid"Not Ikea", "nothing from Amazon"

Don't interview the designer. If the brief is "acoustic panels for a lobby," that's enough to start searching. You can clarify after showing initial results if needed ("I found options in fabric, felt, and wood slat — any preference?").

Step 2: Research

Search the web for products matching the brief. Use multiple targeted queries to cover different angles:

Search strategy

For a brief like "round dining table, walnut, under $3,000":

  1. Category + material search: round walnut dining table
  2. Design-focused search: best round wood dining tables architects designers
  3. Trade/contract search: contract round dining table solid wood specifications (for commercial projects)
  4. Specific brand searches if the designer mentioned preferences: Muuto round table, HAY dining table
  5. Sustainability search if relevant: FSC certified round dining table

Run 3-5 searches depending on brief complexity. Aim for breadth — different price points, brands, styles.

For each candidate found

Attempt to fetch the product page with WebFetch to extract full specs. If the page is JS-rendered and returns no data:

  • Use the search result only to identify the candidate and locate another current, authoritative source.
  • Never fill price, availability, lead time, dimensions, finishes, certifications, or other purchasing facts from model memory.
  • Label any volatile fact without a current manufacturer, authorized-dealer, or certification-registry source as Not verified; do not turn a search snippet into a confirmed fact.

For every price, availability, lead-time, finish, dimension, and certification claim, retain the source URL and access date. Prefer the manufacturer's current product page or price list; use an authorized dealer only when the manufacturer does not publish the fact. A candidate may remain useful with Not verified fields, but the shortlist must make those gaps visible.

Target: 6-10 candidates that genuinely match the brief. Don't pad the list with weak matches.

Step 3: Present Candidates

Show results as a numbered shortlist with enough detail to evaluate:

text
Synthetic formatting input only:
Example Product A | Example Manufacturer | quantity 2 | supplied specification pending
Presentation rules
  • Lead with the summary table if there are 6+ candidates — designers scan visually
  • Include "Why" for each — explain why this product matches the brief, and flag any compromises
  • Flag trade-offs honestly — "veneer not solid", "over budget but worth seeing", "long lead time"
  • Don't oversell — if a product is a weak match, say so or don't include it
  • Group by angle if useful — "Budget options", "Premium picks", "Fastest delivery"
Show full SKILL.md (729 more words)Show less

Step 4: Save to the project library

When the designer picks candidates ("save 1, 3, and 5"), prepare rows for the nearest project-root product-library.csv. A project root is the nearest ancestor containing PROJECT.md; do not create a library outside one.

Row format

Read ../../schema/product-schema.md for the exact 33-column row contract and ../../schema/csv-conventions.md for local-file rules. Preview all selected products and the target path, then use existing exact authorization or ask once for the missing approval. After approval, serialize all complete rows as one JSON array and hand one complete batch to product-library's native append operation. That owner validates current state and the full batch before guarded publication and fresh readback; never loop per row or hand-edit persistent CSV.

Skill-specific column values:

  • AG (Source): research
  • AF (Status): saved
  • AD (Tags): From brief context (e.g. "lobby-reno, walnut")
  • AE (Notes): The "Why" reasoning from the presentation
  • T (Selected Color/Finish): Blank (designer hasn't configured yet)
After saving
✓ Saved 3 products to your library (rows 48-50).
  Tagged: lobby-reno, walnut

Want me to refine the search? Different style, budget, or materials?

Step 5 (Optional): Iterate

The designer may want to refine:

  • "More like #1 but cheaper" → Search for alternatives in that style/brand tier
  • "What about outdoor versions?" → New search with added constraint
  • "Can you find the spec sheet PDF for #3?" → Search for manufacturer cut sheet
  • "Compare #1 and #3 side by side" → Detailed comparison
  • "Any of these have GREENGUARD?" → Check certifications for the shortlist

Each iteration can add more products to the library.

Conversation Style

  • Don't over-ask before searching. A one-line brief is enough to start.
  • Show results, then refine. It's faster to react to real options than to specify everything upfront.
  • Be opinionated. The designer wants a knowledgeable research assistant, not a search engine. Flag the best options, note trade-offs, suggest alternatives.
  • Know the industry. Reference relevant brands, designers, trade platforms. Understand contract vs. residential, COM/COL, lead times, certifications.

Notes

  • JS-rendered product pages are common (Hem, Muuto, Vitra, etc.). If native retrieval returns no data, use search results only for candidate discovery and seek a current authoritative source; purchasing facts remain Not verified. Do not fill them from general knowledge.
  • The library is shared. Products from this skill live alongside bulk-fetch imports and PDF extractions. The Source field (research) identifies where each row came from.

Original product evidence

Retrieve exact selected manufacturer/product/variant facts from original documents for the task. Example data is synthetic and never evidence. Do not copy product facts, certifications, prices or vendor format definitions into the plugin as reusable reference knowledge. Preserve unresolved values and distinguish representative imagery from the exact selected variant.

Native output and owner handoff

A requested durable authored report uses receive's native document owner for exact coordinate-based placement, query and registration; do not compose project folders from labels. One-off reports use only their explicitly authorized destination and require no studio/project setup. Canonical adopted revisions and reusable library saves remain with their owners. Existing exact authorization persists; obtain only missing material scope or native permission.

For any output this skill actually saves or edits, apply the native mutation sequence to its complete affected set. Retain all original bytes/access, source/identity guards, complete prepared output and absence/preconditions; finish durable saves and independently reread all retained/prepared content and access before the first publisher. Preserve unrelated data and actual workbook features when applicable. Reopen every actual destination's complete bytes and mode/applicable ownership/ACLs, and verify changes, source lineage and protected originals before reporting completion. Correct bytes, a creation-mode argument or an emitted receipt alone is insufficient. Unsupported protection or uncertain publication stays blocked/pending with recovery evidence.

Use native capabilities suited to the selected mode; process execution is optional when the chosen method needs it. No Arch Studio runner, executable download or source reconstruction is required. Read-only/inline work does not need write capability. Report actual research/extraction, validated proposal and any independently verified owner save separately; do not claim an owner handoff has completed without its actual evidence.

Native workbook preservation comparison

When an explicitly selected before/after native .xlsx or .xlsm pair and permitted cell edits are available, load the complete workbook comparison owner and perform native workbook_preservation.compare with actual ZIP/XML inspection. Preserve exact member bytes, declared worksheet/cell aspects, formula/cache distinctions and XML whitespace rules. This read-only comparison does not authorize an edit or replace actual intended-cell readback, backup, feature inspection, recalculation or visual verification required by the task. Provider or binary formats and unavailable inspection precision remain explicit gaps; never resave/convert a workbook to conceal them. No Arch Studio helper or process runtime is mandatory.

© AlpacaLabsLLC, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files in skills/product-research of AlpacaLabsLLC/skills-for-architects.

  • SKILL.md
  • README.md
  • host-contract.json

Open the folder on GitHubat commit 657bfd5

Compare with similar skills

Product Research next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Product Research compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Product Research this skillAlpacaLabsLLC/skills-for-architects373—~3.7kAutomated safety check: NotesMIT
Data Table Managern8n-io/n8n207k—~2.3kAutomated safety check: PassCustom licence
Instrument Data To Allotropeaws-samples/amazon-bedrock-agents-healthcare-lifesciences2742 repos~2.7kAutomated safety check: PassApache-2.0
Abuse Hunternexu-io/harness-engineering-guide664—~1.9kAutomated safety check: PassMIT
Intelligence Requirements BuilderTracecatHQ/tracecat3.8k—~6kAutomated safety check: PassMIT
Markitshift-labs-ai/markit1.3k—~299Automated safety check: PassMIT

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Questions about Product Research

What does Product Research do?

Find and compare current FF&E candidates from a design brief, with sourced purchasing facts and optional CSV-library save. Product Research is an agent skill from AlpacaLabsLLC/skills-for-architects. Find and compare current FF&E candidates from a design brief, with sourced purchasing facts and optional CSV-library save.

When should I use Product Research?

Product Research fits situations like: source products; not to match from an image; pair coordinating items.

How do I install Product Research in Claude Code?

Run `npx skills add AlpacaLabsLLC/skills-for-architects --skill product-research -a claude-code`. Or copy the skill folder (skills/product-research in AlpacaLabsLLC/skills-for-architects) into .claude/skills/product-research in your project. Claude Code loads it when a task matches its description.

How do I install Product Research in Codex?

Run `npx skills add AlpacaLabsLLC/skills-for-architects --skill product-research -a codex`. Or copy the skill folder (skills/product-research in AlpacaLabsLLC/skills-for-architects) into .agents/skills/product-research in your project. Codex loads it when a task matches its description.

Can I use Product Research in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add AlpacaLabsLLC/skills-for-architects --skill product-research -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/product-research, .gemini/skills/product-research, .github/skills/product-research and .opencode/skills/product-research in your project.

What does Product Research need to run?

SKILL.md names no scripts, command-line tools or credentials: Product Research is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash, Glob, Grep, WebFetch, WebSearch, AskUserQuestion.

Does Product Research access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Product Research safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Product Research use?

Product Research is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Product Research use?

About 3.7k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Product Research?

Skills that share tags, products or a category with Product Research: Data Table Manager (n8n-io/n8n, 207k stars), Instrument Data To Allotrope (aws-samples/amazon-bedrock-agents-healthcare-lifesciences, 274 stars), Abuse Hunter (nexu-io/harness-engineering-guide, 664 stars) and Intelligence Requirements Builder (TracecatHQ/tracecat, 3.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Product Research?

AlpacaLabsLLC (a GitHub organization) maintains it in AlpacaLabsLLC/skills-for-architects, which has 373 GitHub stars. The repository holds 60 skills in this directory. The repository was last updated on October 5, 2026.

Source: AlpacaLabsLLC/skills-for-architects on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.