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.
git clone --depth 1 https://github.com/catch-the-wave/fullstack-ios-claude-skillsWrote 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.
[](https://agentmods.dev/commands/catch-the-wave/fullstack-ios-claude-skills/b2c-segments)<a href="https://agentmods.dev/commands/catch-the-wave/fullstack-ios-claude-skills/b2c-segments"><img src="https://agentmods.dev/badge/commands/catch-the-wave/fullstack-ios-claude-skills/b2c-segments.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00014 | $0.00992 |
| Opus 5 | $0.00007 | $0.00496 |
| Sonnet 5 | $0.00003 | $0.00198 |
| Haiku 4.5 | $0.00001 | $0.00099 |
Grade A, and why
b2c-segments 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 7d 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.
How it starts
The opening of the file, as written. The whole thing — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
B2C Segment Analysis
You are a professional product strategist and analyst working strictly according to the Advanced Jobs To Be Done (AJTBD) methodology. Based on a brief description of a B2C product, perform an analysis and select the 5 most attractive segments for launching or scaling the product.
Input Block
Product: %insert product description here% Product website: %insert link to website or AppStore/PlayMarket page here%
Step 1. Build 7-10 Hypothetical B2C Segments (but don't output them)
Each segment should:
-
Be united by a set of 1–4 Core Jobs
- Core Job is a job for which a company or person consciously hires a solution and is willing to pay.
-
Necessarily contain one Big Job
- Big Job is a higher level of motivation - the reason why a person performs Core Jobs at all. This can be a life goal, transition, ambition, or state they strive for.
-
Differ by:
- Context of job execution: life situation, role, life changes, external trigger
- Customer role: e.g., HR, founder, mom, marketer, designer, product manager
- Performance criteria: e.g., "quickly", "cheaply", "without errors", "prestigiously", "simply"
Important: A segment is not one job, not a demographic group, and not a role. It's people with a similar set of jobs and similar performance criteria.
Step 2. Analyze Each Segment by 4 Parameters (but don't output them)
-
TAM / SAM / SOM
- TAM (Total Addressable Market): the entire market where such jobs are performed
- SAM (Serviceable Available Market): part of TAM that can be served with the current business model
- SOM (Serviceable Obtainable Market): part of SAM that can realistically be captured in 1–2 years considering resources and channels
-
Customer Value
- How well the product can close a pack of jobs compared to current solutions
- Are there gaps in the critical sequence of jobs (CSJ) that the product can eliminate
- Does the product work turnkey or only at a low level
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.
- 7d ago First seen · 114 lines · 14 tokens per session scan A b05da734dcd8
b2c-segments is a command published in the GitHub repository catch-the-wave/fullstack-ios-claude-skills (5 stars, last pushed 8mo ago), licensed MIT. It adds 14 tokens to every session and 992 once invoked, about $0.0001 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.
Other commands, from other repositories
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clarify
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specify
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converge
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implement
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analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.