market-comp-analysis

market-comp-analysis is a skill for Claude Code from Fusion-Data-Company/bristol-os. It costs 73 tokens per session (607 once invoked), scanned A, original, MIT.

A real-estate market study that compares nearby rental properties and examines rents, occupancy, new housing supply, leasing speed, sales, and cap rates. A cap rate is a property's annual operating income compared with its purchase price.

In plain words
What is it for?
Use it to build a set of comparable properties, track rent and vacancy trends, review upcoming supply, and assess competition behind an investment deal.
Why use it?
It gathers the market facts needed to judge whether a property can achieve its planned rent and how much competition or oversupply it may face.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the bristol-os plugin — 14 skills shipped together

Good fit Use it to build a set of comparable properties, track rent and vacancy trends, review upcoming supply, and assess competition behind an investment deal.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/fusion-data-company/bristol-os/market-comp-analysis
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 Fusion-Data-Company/bristol-os --skill market-comp-analysis
Clone the repo
git clone --depth 1 https://github.com/Fusion-Data-Company/bristol-os

Made for: Claude Code.

Or install bristol-os, the plugin that ships this one along with the rest of its 14 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 market-comp-analysis

README.md
[![agentmods](https://agentmods.dev/badge/skills/fusion-data-company/bristol-os/market-comp-analysis/github.svg)](https://agentmods.dev/skills/fusion-data-company/bristol-os/market-comp-analysis)
Your own site
<a href="https://agentmods.dev/skills/fusion-data-company/bristol-os/market-comp-analysis"><img src="https://agentmods.dev/badge/skills/fusion-data-company/bristol-os/market-comp-analysis/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 market-comp-analysis

Your own site · 80×15
<a href="https://agentmods.dev/skills/fusion-data-company/bristol-os/market-comp-analysis"><img src="https://agentmods.dev/badge/skills/fusion-data-company/bristol-os/market-comp-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 73 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 607 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 $0.00073 $0.00607
Opus 5 $0.00036 $0.00303
Sonnet 5 $0.00015 $0.00121
Haiku 4.5 $0.00007 $0.00061

Measured 12d ago against content hash 32c6d9b048d3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

market-comp-analysis 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.

plugins/bristol-os/skills/market-comp-analysis/SKILL.md · 41 lines

How it starts

The opening of the file, as written. The whole thing — 41 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Market & Comp Analysis

Build the market picture behind a deal: what rents are achievable, what's competing, where the market is heading.

When to use

"Pull comps for [submarket]," "build me a market study," "what are rents/cap rates doing in [market]," "who are the competitive properties near [site]?"

Inputs

  • Subject property/site location and product type.
  • Unit mix if known (studio/1BR/2BR/3BR), target rent band if any.
  • Radius or named submarket for the comp set.

What to assemble (cite sources + dates)

  1. Comparable set — 4–8 competing communities: name, location, year built, units, unit mix, current asking rents (by unit type and per SF), concessions, occupancy. Note the source for each.
  2. Rent trend — direction and rate of rent growth over the last 1–3 years for the submarket.
  3. Occupancy / vacancy — current and trend.
  4. Supply pipeline — units under construction and planned nearby; expected delivery timing; absorption pace. Call out oversupply risk explicitly.
  5. Cap-rate & sales trend — recent multifamily sales/cap rates in the market if available; direction of movement.
  6. Concessions & lease-up reads — what new deliveries are offering to lease up.

Tools

  • Yardi Matrix connector if connected — best for rents, comps, pipeline, ownership.
  • Otherwise built-in web search / Tavily / Exa: pull from property marketing sites, market reports (CBRE/JLL/Cushman/Marcus & Millichap), census/BLS, local news on new developments.
  • The user can also paste CoStar/RealPage exports — fold those in and cite them as Bristol-provided.

Output

  • Market study using bristol-os/templates/market-study.md, saved to the deal folder.
  • Comp table (clean, sortable): community, rents by type, $/SF, occupancy, vintage, distance.
  • Read on achievable rent for the subject + the supply risk verdict.
  • Bottom line: is the market supportive of this deal's rent and absorption assumptions?

Accuracy

  • Every comp and number gets a source + date. If a rent is an estimate, label it.
  • Don't average across non-comparable product — note when comps are imperfect.
  • Distinguish asking rents (advertised) from effective rents (after concessions) and say which you used.

Read the full file on GitHub · 41 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. 12d ago First seen · 41 lines · 73 tokens per session scan A 32c6d9b048d3

Subscribe to this mod's changes

market-comp-analysis is a skill published in the GitHub repository Fusion-Data-Company/bristol-os (1 stars, last pushed 2mo ago), licensed MIT. It adds 73 tokens to every session and 607 once invoked, about $0.0004 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 2026-08-31.

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