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 skills add aaronjmars/aeon-agent --skill narrative-convergencegit clone --depth 1 https://github.com/aaronjmars/aeon-agentWrote 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/aaronjmars/aeon-agent/narrative-convergence)<a href="https://agentmods.dev/skills/aaronjmars/aeon-agent/narrative-convergence"><img src="https://agentmods.dev/badge/skills/aaronjmars/aeon-agent/narrative-convergence/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/skills/aaronjmars/aeon-agent/narrative-convergence"><img src="https://agentmods.dev/badge/skills/aaronjmars/aeon-agent/narrative-convergence.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 | $0.00037 | $0.02121 |
| Opus 5 | $0.00018 | $0.01060 |
| Sonnet 5 | $0.00007 | $0.00424 |
| Haiku 4.5 | $0.00004 | $0.00212 |
Grade A, and why
narrative-convergence 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.
This is a copy
100% identical to narrative-convergence — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.
${var} — Optional entity or theme filter (e.g. "Anthropic", "coordination markets"). If empty, scans all skill output categories.
Today is ${today}. Read memory/MEMORY.md before starting.
Voice
If soul/SOUL.md and soul/STYLE.md exist and are populated, read them and match the operator's voice when drafting the write angles and hook lines (step 5) and the notification. Otherwise use a clear, direct, neutral tone — short, declarative, position-first.
Why this skill exists
topic-momentum surfaces content gaps by scanning the content-discovery pipeline against article history. It works well for pre-tagged narrative categories.
This skill does something different: it detects emergent cross-skill convergence — when independent operational skills (security scanners, market trackers, sector pulses, etc.) all surface the same entity, company, protocol, or theme within 48h, without any prior coordination. That kind of convergence is a higher-signal indicator than any single source — it often precedes a breakout narrative. Example: a security skill flags a company's automated-vulnerability work, a social digest catches that same company announcing a major deal, and a market tracker notes a related fraud-prevention win — three independent skills, one entity, in 48h. That bleedthrough is the signal. This skill catches it automatically.
Config
The signal-category map is operator-editable and lives in memory/topics/signal-categories.md. If the file doesn't exist, create the seed below and continue. The categories are what let the skill measure cross-category diversity (the core of the convergence score) — edit them to match the skills you actually run.
# Signal Categories
## Housekeeping (excluded — no external signals)
config-validator, janitor, frequency-guard, heartbeat, memory-flush,
memory-dedupe, skill-health, skill-repair, self-improve,
cost-report, fleet-scorecard, fleet-control, repo-scanner, narrative-convergence
## Signal categories (skill → category)
| Category | Skills |
|----------|--------|
| market | market-context, token-pick, token-movers, rwa-pulse, defi-overview |
| social | tweet-roundup, list-digest, narrative-tracker, remix-tweets, refresh-x |
| ecosystem | github-issues, github-trending, project-lens, builder-map, external-feature, milestone-tracker |
| sector | mcp-pulse, compute-pulse, x402-monitor, agent-displacement, pm-pulse |
| security | vuln-scanner, vuln-tracker, disclosure-tracker, pvr-watchlist, pvr-triage |
| research | paper-pick, article, idea-validator, idea-pipeline |
| opportunity | startup-idea, deal-flow, launch-radar |
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 · 196 lines · 37 tokens per session scan A 0baaedaf6f84
narrative-convergence is a skill published in the GitHub repository aaronjmars/aeon-agent (11 stars, last pushed today), licensed MIT. It adds 37 tokens to every session and 2,121 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to narrative-convergence, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…