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/aashwindev/convergence/skillnpx skills add aashwindev/convergence --skill skillgit clone --depth 1 https://github.com/aashwindev/convergenceWhat 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 | $0.00122 | $0.09260 |
| Opus 5 | $0.00061 | $0.04630 |
| Sonnet 5 | $0.00024 | $0.01852 |
| Haiku 4.5 | $0.00012 | $0.00926 |
Grade A, and why
building-helios-frontends scanned grade A with 1 finding 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 yesterday.
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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
const blob = await fetch(scene.imageUrl).then((r) => r.blob()); 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.
- yesterday First seen · 639 lines · 122 tokens per session scan A b5a7c2e987ef
building-helios-frontends is a skill published in the GitHub repository aashwindev/convergence (2 stars, last pushed 1mo ago), with no licence file. It adds 122 tokens to every session and 9,260 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
testing-validation
Use when selecting, running, or fixing WorldForge validation: pytest, coverage, ruff, generated provider docs, MkDocs strict build, package contract, CI failures, and release gates. Produces the smallest credible command set first, then escalates to full validation when public behavior changes.
public-docs-release
Use for WorldForge README, docs, changelog, generated provider docs, MkDocs navigation, version/release metadata, public positioning, and release or publish readiness checks. Keeps public surfaces synchronized without hype or generated-doc drift.
optional-runtime-smokes
Use for LeWorldModel, GR00T, LeRobot, PushT robotics showcase, real-checkpoint smoke scripts, checkpoint building, and host-owned optional runtime dependencies. Keeps real-runtime validation explicit without adding heavy ML/robotics packages or artifacts to the base project.
persistence-state
Use for WorldForge local state: run workspaces and artifacts under .worldforge/ (run manifests, evidence bundles, retention/prune), the WorldForge(statedir=...) directory, and JSON-native artifact validation. The symbolic World JSON store and the worldforge world CLI were removed; there is no world persistence.…
provider-adapter-development
Use for WorldForge provider work: adding adapters, changing capability declarations, promoting scaffolds, debugging provider failures, updating provider catalog docs, or touching LeWorldModel, GR00T, LeRobot, Cosmos-Policy, JEPA, Genie, or JEPA-WMS. Ensures capabilities remain truthful and optional runtimes stay…
evaluation-benchmarking
Use for WorldForge evaluation suites, benchmark harness changes, benchmark input fixtures, budget gates, report rendering, metrics semantics, and any claims based on benchmark or evaluation output. Keeps benchmark/eval artifacts deterministic, coherent, and claim-bounded.