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 commands/aegntic/cldcde/emergent-capabilitiesgit clone --depth 1 https://github.com/aegntic/cldcdeWrote 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/aegntic/cldcde/emergent-capabilities)<a href="https://agentmods.dev/commands/aegntic/cldcde/emergent-capabilities"><img src="https://agentmods.dev/badge/commands/aegntic/cldcde/emergent-capabilities.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 | $0.00026 | $0.02938 |
| Opus 5 | $0.00013 | $0.01469 |
| Sonnet 5 | $0.00005 | $0.00588 |
| Haiku 4.5 | $0.00003 | $0.00294 |
Grade A, and why
emergent-capabilities 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 5d 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 — 381 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Emergent Capability Suite by ae.ltd
ᵖᵒʷᵉʳᵉᵈ ᵇʸ ᵃᵉᵍⁿᵗᶦᶜ ᵉᶜᵒˢʸˢᵗᵉᵐˢ ʳᵘᵗʰˡᵉˢˢˡʸ ᵈᵉᵛᵉˡᵒᵖᵉᵈ ᵇʸ ae.ˡᵗᵈ
Advanced meta-skill ecosystem that evolves new capabilities through intelligent skill synthesis, pattern recognition, and complex adaptive systems modeling.
Overview
The Emergent Capability Suite represents the cutting edge of AI capability evolution, transforming existing skills into new, more powerful emergent capabilities through sophisticated pattern recognition, synthesis algorithms, and adaptive systems modeling. This suite goes beyond traditional automation to create genuinely new capabilities that evolve and improve over time.
Core Capabilities
- Emergent Capability Discovery: Identify and develop new capabilities from skill combinations
- Complex Adaptive Systems: Model and evolve capabilities that adapt to changing requirements
- Pattern Recognition Engine: Advanced algorithms for identifying high-impact skill synergies
- Meta-Skill Ecosystem: Self-improving capabilities that evolve based on usage patterns
- Cross-Platform Integration: Seamless capability development across multiple AI platforms
- Enterprise-Grade Evolution: Scalable capability development for enterprise workflows
Commands
/emergent-capabilities discover [parameters]
Discover new emergent capabilities from existing skill combinations and usage patterns.
Usage Examples:
# Discover automation capabilities
/emergent-capabilities discover action=discover capability_type=automation complexity_level=emergent
# Discover cross-platform capabilities
/emergent-capabilities discover action=discover ecosystem_scope=cross-platform evolution_target=integration
# Discover complex workflow capabilities
/emergent-capabilities discover action=discover capability_type=workflow complexity_level=complex skill_combination='["ai-ml-engineering-pack","testing-automation","git-commit-smart"]'
/emergent-capabilities synthesize [parameters]
Synthesize new capabilities by combining existing skills with intelligent optimization.
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.
- 5d ago First seen · 381 lines · 26 tokens per session scan A d2dc9ad15acf
emergent-capabilities is a command published in the GitHub repository aegntic/cldcde (11 stars, last pushed 9d ago), licensed MIT. It adds 26 tokens to every session and 2,938 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 2026-08-30.
Other commands, from other repositories
seed
Load fixture teams + products into the local D1 database.
smoke
Deploy a versioned preview, hit smoke endpoints, print a status table.
migrate
Apply pending D1 migrations to local (default) or remote.
deploy-preview
Build + deploy a versioned preview; print the preview URL.
scriptwriter-draft
Create a writers' room with a seed prompt and (optionally) contribute the first scene. Co-brainstorm space with signed contributions and a live SSE stream for peers.
scriptwriter-draw
Draw a random chaos card from the 13-card deck — a plot-twist prompt the user can use as a scene seed, a basistext for an RRR cascade, or a riff for a room contribution.