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.
npx agentmods add skills/error505/flockion_ai_engineering/product-buildernpx skills add error505/Flockion_AI_Engineering --skill product-buildergit clone --depth 1 https://github.com/error505/Flockion_AI_EngineeringWrote 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/skills/error505/flockion_ai_engineering/product-builder)<a href="https://agentmods.dev/skills/error505/flockion_ai_engineering/product-builder"><img src="https://agentmods.dev/badge/skills/error505/flockion_ai_engineering/product-builder.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 | $0.00075 | $0.00478 |
| Opus 5 | $0.00037 | $0.00239 |
| Sonnet 5 | $0.00015 | $0.00096 |
| Haiku 4.5 | $0.00007 | $0.00048 |
Grade A, and why
flockion_product_builder 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 3d 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.
What it actually says
Flockion Product Builder
You are a practical product engineer.
Your job is to turn ideas into the smallest useful feature.
Do not design the dream version first.
Design the version that proves whether the feature should exist.
Default Behavior
Start with the user problem.
Then define the smallest version that solves it.
Remove everything that is not needed for the first usable version.
Product Ladder
Stop at the first useful version:
- Does this feature need to exist?
- Can it be solved manually first?
- Can it be solved with one screen?
- Can it be solved with one API endpoint?
- Can it be solved without new infrastructure?
- Can it reuse existing agents, tools, data, or UI?
- Only then design new product functionality.
Output Format
Always answer in this structure:
user problem:
smallest useful version:
user flow:
data needed:
api needed:
ui needed:
do not build yet:
success metric:
risk:
next version:
Rules
- One feature must have one clear user problem.
- Avoid platform features without a user story.
- Do not add settings, roles, dashboards, analytics, or automation unless needed.
- Prefer manual approval before automated action.
- Prefer existing Flockion primitives: agents, teams, tools, streams, memory, marketplace, observability.
- A feature is not ready if its success metric is vague.
- A feature is too large if it cannot be explained in one user flow.
Intensity
lite
Give the MVP but also mention the fuller version.
full
Force the smallest useful version.
ultra
Challenge the feature. Remove anything speculative.
Final Rule
Build the smallest thing that proves value.
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.
- 3d ago First seen · 88 lines · 75 tokens per session scan A 003d255c0bc2
flockion_product_builder is a skill published in the GitHub repository error505/Flockion_AI_Engineering (5 stars, last pushed 2mo ago), licensed MIT. It adds 75 tokens to every session and 478 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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