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/ishwarjha/lumen-product-managementWrote 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/agents/ishwarjha/lumen-product-management/narrative-engine)<a href="https://agentmods.dev/agents/ishwarjha/lumen-product-management/narrative-engine"><img src="https://agentmods.dev/badge/agents/ishwarjha/lumen-product-management/narrative-engine/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.
<a href="https://agentmods.dev/agents/ishwarjha/lumen-product-management/narrative-engine"><img src="https://agentmods.dev/badge/agents/ishwarjha/lumen-product-management/narrative-engine.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00034 | $0.00623 |
| Opus 5 | $0.00017 | $0.00311 |
| Sonnet 5 | $0.00007 | $0.00125 |
| Haiku 4.5 | $0.00003 | $0.00062 |
Grade A, and why
narrative_engine 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 9d 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 9d ago First seen · 75 lines · 34 tokens per session scan A 3051af49e809
narrative_engine is an agent published in the GitHub repository ishwarjha/lumen-product-management (15 stars, last pushed 5mo ago), with no licence file. It adds 34 tokens to every session and 623 once invoked, about $0.0002 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 2026-08-30.
Other agents, from other repositories
100x-engineer
Autonomous full-stack engineer that takes a requirement from idea to production-ready code. Researches best approaches, prototypes unknowns, builds a comprehensive plan broken into waves of parallel tasks, executes via sub-agents, tests everything, audits for security, and delivers a final handoff report with any…
gap-finder
Analyzes a venture's AI usage across 10 production functions and identifies high-value gaps where AI could create value but currently isn't being used. Generates specific, actionable recommendations grounded in how other firms have deployed AI. Use this agent after the venture-scanner has inventoried projects, when…
priority-scorer
Scores and ranks AI mapping opportunities by revenue impact, capital reduction, and implementation ease. Produces a prioritized action plan with specific next steps. Use this agent after the gap-finder has identified opportunities across ventures, when the user runs /map-score, when prioritizing AI deployment…
venture-scanner
Explores a user's workspace to discover and inventory all projects, businesses, and ventures. Maps organizational structure, identifies revenue streams, existing automation, and AI integrations. Use this agent when you need to understand the full scope of what someone is building before performing an AI mapping audit.…
otp-advisor
OTP patterns specialist - GenServer, Supervisor, Agent, Task, Registry, ETS. Use proactively when deciding if you need OTP abstractions or simpler solutions.
demand-generation
Demand Generation (CMO). Owns plugins/demand-generation/ and nothing else. Delegate work in this department's remit here.