A real report, written by 64 · Market Size & Timing, run against this repo — dogfood output, committed unedited. This is the artifact every brief ends in: findings that cite their evidence, ranked by severity, with a fix sketch each.
Produced by brief 64 · Market Size & Timing, run against this repo's own venture: goal-prompts — a catalog of structured audit briefs for coding agents. Bottom-up from NICHE.md + COMPETITORS.md; DEMAND.md fixes where WTP actually sits. All sources accessed 2026-07-10 unless dated otherwise. Directly-fetched primaries unmarked; analyst/market figures and web-search synthesis marked [secondary].
Date: 2026-07-10
This market has two floors and they are priced differently, so the report models both and never lets one launder the other. The catalog layer goal-prompts occupies has a dollar-TAM of $0 — it is MIT/free, and every rival is too (DEMAND.md, COMPETITORS.md price row); the "market" there is attention, denominated in stars and installs, not revenue. The monetizable market is one layer over — the team-audit / managed-review outcome DEMAND.md located WTP in — and that is where the arithmetic below spends its effort.
Buyer unit (dollar side): not the individual developer. DEMAND.md's central finding is that the individual dev adopts but does not pay, and NICHE.md's buyer≠user split says the pen is held by a DevEx/platform lead or eng manager at a software team that already pays for AI coding tooling and buys outcomes (CodeRabbit-shaped), not text. For goal-prompts specifically that buyer resolves into two SKUs already scaffolded in REVENUE.md: (A) a team-audit / private-catalog engagement (setup + custom linted briefs + standing CI audits + support — flat fee, deliberately not per-seat metered), and (B) a sponsored/collab playbook bought by a dev-tool marketing budget against goal-prompts' audience.
Annual-value hypothesis per unit — anchored on what the team-audit outcome actually commands today, revealed by CodeRabbit's own ARR ÷ customers:
| Anchor | Arithmetic | $/customer/yr | Source |
|---|---|---|---|
| CodeRabbit, Sept 2025 | $15M ARR ÷ 8,000 businesses | ≈ $1,875 | techcrunch.com/2025/09/16/coderabbit-raises-60m-valuing-the-2-year-old-ai-code-review-startup-at-550m/ (fetched) |
| CodeRabbit, 2026 (all customers) | $40M ARR ÷ 15,000 customers | ≈ $2,667 | Sacra (fetched) + coderabbit.ai hero (COMPETITORS.md) |
| CodeRabbit, 2026 (paying only) | $40M ARR ÷ 8,000+ paying | ≈ $5,000 | Sacra (fetched) |
So the team-audit outcome commands ≈ $1,900–5,000/customer/yr in the open market. goal-prompts' lighter offering (setup + support + private catalog, not a managed PR pipeline) plausibly captures a fraction: $1,000–3,000/team/yr (SKU A). SKU B (sponsorship) anchors on dev-media placement rates and VoltAgent's sponsor-funded model (COMPETITORS.md): $500–2,500/placement, a handful/yr.
Countable proxies gathered (someone could enumerate these):
| Countable | Value | Date | Source |
|---|---|---|---|
| Developers on GitHub | 180M+ (+36M/yr, +23%, "one/second") | Octoverse 2025 | github.blog/…octoverse-a-new-developer… (fetched) |
| GitHub Copilot total users / paid | ~20M / 4.7M paid (+75% YoY) | Jul 2025 / Jan 2026 | getpanto.ai, axis-intelligence.com [secondary] |
| Copilot enterprise customers | ~77,000 | FY2024 | getpanto.ai [secondary] |
| Cursor active devs / businesses / ARR | ~4M / 50,000 / $2B ARR | Dec 2025–Apr 2026 | getlatka.com, getpanto.ai [secondary]; ARR per NICHE.md (techcrunch Apr 2026) |
| Claude Code weekly-active devs | 2M+ (doubled since Jan 1 2026) | Feb 2026 | Anthropic via linkedin.com/…gptproto [secondary]; run-rate >$2.5B primary (NICHE.md) |
| CodeRabbit customers / paying | 15,000 / 8,000+ paying | 2026 / Sept 2025 | coderabbit.ai, techcrunch, Sacra (fetched) |
| Incumbent catalog stars (attention TAM) | ~139k combined | 2026-07-10 | GitHub API (COMPETITORS.md, fetched) |
| MCP monthly SDK downloads / servers | 97M/mo / 10k+ | Mar 2026 | digitalapplied.com [secondary]; registry primary (NICHE.md) |
| goal-prompts stars | 0 | 2026-07-10 | github.com/GhostlyGawd/goal-prompts |
| Layer | What it is | Dollar size | How measured |
|---|---|---|---|
| Catalog TAM (where goal-prompts sits) | Free, MIT audit-brief catalogs | $0 | Attention: ~139k combined stars on the four incumbents (awesome-claude-code 49,729 + wshobson 37,762 + aitmpl 28,745 + VoltAgent 23,154 — COMPETITORS.md). goal-prompts = 0. |
| Monetizable SAM (one layer over) | AI code review / team-audit outcome | $400–600M ARR narrow [secondary]; served proxy CodeRabbit $40M + Greptile + Qodo | Dollars: per-seat/credit subscriptions to teams |
The number to never blur: the catalog TAM is $0 in revenue. Everything monetizable requires crossing into the layer over, which is what the funnel below models.
goal-prompts is at 0 stars / 0 forks today (COMPETITORS.md). Every dollar is gated on first earning distribution, so the model is an honest funnel, not a TAM slice. Four inputs, each a range (bear → bull):
Step 1 — Installs reached in the wedge. Ceiling anchored on comparable catalogs: awesome-claude-code did 0→49,729★ in ~15 months, but that is the outlier; the base rate is a catalog that never clears 1,000. A 0★ entrant executing distribution well:
Step 2 — Share of installs that are a team with budget. Copilot converts ~20M users → 4.7M paid (~23% to any paid, first-party with a credit-card wall); Cursor ~1M DAU → 50k businesses. A free catalog with no wall and near-zero "I'd pay" language (DEMAND.md) is far below that: assume 2% → 5% of installs are an org that would consider a paid engagement.
Step 3 — Conversion of those teams to a paid engagement. Free-catalog→paid-adjacent conversion is essentially unmeasured and, per DEMAND.md's silence test, near-zero today: assume 5% → 20%.
Step 4 — × annual value = $1,000 → $3,000/team/yr (SKU A, from Phase 1).
Worked lines:
| Installs | × team-share | × convert | = teams | × $/yr | SKU A | + Sponsorship (SKU B) | Year total | |
|---|---|---|---|---|---|---|---|---|
| Y1 bear | 1,000 | 2% = 20 | 5% = 1 | 1 | $1,000 | $1,000 | ~$0–2k (1 backer) | ≈ $0–3k |
| Y1 bull | 5,000 | 5% = 250 | 20% = 50 | 50 | $3,000 | $150,000 | 4 × $2,000 = $8k | ≈ $158k |
| Y2 bear | 5,000 | 2% = 100 | 5% = 5 | 5 | $1,000 | $5,000 | ~$2k | ≈ $7k |
| Y2 bull | 25,000 | 5% = 1,250 | 20% = 250 | 250 | $3,000 | $750,000 | 12 × $2,500 = $30k | ≈ $780k |
Obtainable market, stated as a range (Phase 3):
Sanity vs top-down: even the Y2 bull ($780k) is 0.13–0.20% of the $400–600M narrow SAM ($780k ÷ $500M = 0.16%). That is an appropriately tiny slice for a 0★ entrant with no PMF proof and a free core — the bottom-up does not overshoot the top-down; the large gap between them is the distribution/conversion chasm, not a modeling error. If the bottom-up had produced 5% of SAM from 0 stars, that would be the vibe the brief warns against.
Growth reading (the countables, directionally): every input is pointing up and to the right. Developers: 180M on GitHub, +36M/yr (+23%), one new every second (Octoverse 2025). AI-coding adoption: ~80% of new GitHub devs used Copilot in week one; Copilot 4.7M paid (+75% YoY); Cursor $0→$2B ARR in <24 months (fastest B2B SaaS ever claimed); Claude Code WAU doubled since Jan 1 2026, run-rate >$2.5B. Money into the exact adjacent layer: CodeRabbit $60M Series B @ $550M (Sept 2025), $40M ARR +700% YoY; Greptile Series A (Benchmark, ~$180M val); Qodo $40M Series A. The rail: MCP 97M SDK downloads/mo (Mar 2026) from ~2M at launch [secondary]. The attention pool: catalog stars 0→49k in 15 months. Nothing here is flat.
Why-now vs. its strongest rebuttal — side by side:
| Why now (bull) | Why not / rebuttal (bear) |
|---|---|
| The buyer got created and funded 2025–26. CodeRabbit went $5M→$40M ARR in 12 months (700%); the team-audit outcome is a proven, growing line item now, not a 2023 hypothesis. | Same wave = platform absorption. Anthropic ships /security-review (Aug 2025), Agent Skills, and dynamic workflows (May 2026); the primitive goal-prompts catalogs is being pulled first-party for free (DEMAND.md Sub-pain C, NICHE.md weather). Why-now for the buyer is why-now for Anthropic to eat it. |
| The distribution rail exists and is neutral. MCP born Nov 2024, donated to the Linux Foundation Dec 2025, 97M downloads/mo — a vendor-neutral, agent-native catalog channel that did not exist three years ago. [secondary] | The rail is owned by the absorbers. MCP registries + the plugin/skill spec are controlled by the same platforms (Anthropic/Cursor/GitHub) that could reprice or bundle the layer overnight (concentration risk, §3). |
| The install base crossed mass adoption. Copilot Free (Dec 2024) → 36M new devs; 2M+ Claude Code WAU. There is finally a large population running agents on their own repos. | WTP stayed at the execution layer, not the catalog. The "now" that made catalogs viable also made them a $0 commodity — 139k stars, all MIT (DEMAND.md). What opened is an attention window, not a revenue one. |
| The field named itself. "Harness/context engineering" is the AI Engineer World's Fair 2026 theme; "audit/brief/evidence" is an unowned register (COMPETITORS.md). Category-noun land-grab is live. | The complaint vocabulary is calm. People who "keep a running doc of prompts" describe a solved-enough papercut, not an open wound (DEMAND.md). Calm papercuts don't open wallets. |
Why not before (constraint check): pre-2024 there was no agent-native distribution rail (MCP is Nov-2024), no mass base of devs running coding agents on their own repos, and no proven team-audit buyer. The prior attempt at "sell the prompt" — PromptBase — stalled at $1.99–9.99, consumer/image-skewed, and is now pivoting away from prompt-sales (COMPETITORS.md [secondary]). The constraint that killed it: prompts are forkable text with no execution/outcome attached and there was no install base to distribute into. Half that constraint is now gone (the rail and the install base exist); the other half is not — prompts are still free/forkable text (the MIT norm is structural, DEMAND.md/REVENUE.md). So the adjacent constraint lifted; the catalog-monetization constraint did not. That asymmetry is the whole investment case and the whole bear case at once.
Mover-advantage verdict: real but narrow and time-boxed — first-mover matters only for the category noun and the post-run loop; on the brief format, fast-follow is the smarter seat.
Reasoning, by what actually compounds:
Concentration risk — five big ones, not a thousand small checks. At the catalog layer the users are a thousand small free installs (no revenue, no concentration). But every monetizable path is dangerously platform-concentrated: every brief run rides Anthropic/Cursor/Copilot metered tokens; the distribution rails (MCP registry, plugin/skill spec) are platform-controlled; and sponsorship revenue (SKU B) concentrates on a handful of dev-tool advertisers. One Anthropic product decision — ship a first-party audit catalog, or change the skill spec — reprices the entire market overnight. This is the opposite of a resilient many-small-buyers market; the repricing power sits with ~5 actors (Anthropic, Anysphere/Cursor, GitHub/Microsoft, and the top sponsors).
The single assumption that most changes the answer: does free-catalog attention convert to paid-adjacent dollars at all (>0%) — Step 3.
It beats even the distribution input (Step 1) as the swing variable, for a specific reason: the two inputs fail differently. Step 1's plausible range is "small vs. medium" (1k vs. 25k installs — a 25× swing on the top line, but still a number). Step 3's bear value is not small — it is structurally zero, and it is the input with the most disconfirming evidence behind it: DEMAND.md's silence test found near-zero "I'd pay for a prompt catalog" language anywhere, and REVENUE.md rules brief-access paywalls both forkable and goodwill-poisoning. If catalog→paid conversion is truly ~0%, then every row of the funnel collapses to $0 of SKU A regardless of how good distribution gets — the "monetizable market one layer over" becomes reachable only by becoming an execution product (a different company, different report), and goal-prompts' entire obtainable market shrinks to sponsorship + gratitude (SKU B + backers), i.e. low-four-to-five figures at best, forever.
Concretely: hold the Y2-bull installs (25,000) and team-share (5%) fixed and vary only conversion:
Distribution (Step 1) is the gate; conversion (Step 3) is the cliff. If I get one number right before spending a dollar, it is whether a single team will pay for the outcome — which is exactly the open question NICHE.md flagged that only real customer conversations can answer.
Honest evidence gaps: goal-prompts' own install/conversion data does not exist (0★, no analytics — REVENUE.md/FUNNEL.md), so Steps 1–3 are reasoned from comparables, not measured. Copilot/Cursor/Claude Code user counts are [secondary] aggregator figures (the vendors publish few hard primaries); the AI-code-review market sizes are [secondary] analyst ranges used only to bound. CodeRabbit's ARR/customer split is the firmest anchor (TechCrunch + Sacra, fetched). Reddit/directory install counts remain unfetchable (consistent with the companion reports).
Report only — do size and timing justify the next brief?