Name: hephaestus-network
Rating: 69.6 (1 reviews)
Author: agentlas-ai

hephaestus-network

Use when the user types $hephaestus-network, /hep-network, or /agentlas-network, mentions @Hephaestus, or asks Agentlas to staff a durable goal from registered Local, owner Cloud, and public Hub agents or teams. The active host LLM staffs each turn; the exact roster remains goal-bound until explicit completion.

Quality

84%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

Low

Low-risk findings worth noting

The canonical home for this skill is hephaestus-network in agentlas-ai/Agentlas-OS

Quality

Content

73%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A technically rigorous, well-sequenced workforce-staffing protocol with strong validation gates and concrete tooling. The main weakness is recurring prohibition restatement that could be condensed for token efficiency.

Suggestions

Consolidate the repeated 'fail closed / never fabricate / do not echo' prohibitions into a single boundary section and reference it, rather than restating them in sections 3, 6, and 7.

Add one fully filled example MCP call (realistic taskBrief/roles/edges values) alongside the signature-only sequence to lift actionability from signature to copy-paste-ready.

Consider moving the detailed execution-receipt field enumeration (section 7) and the model-allocation policy details (section 5) into reference files to reduce body length while keeping the workflow overview inline.

Dimension	Reasoning	Score
Conciseness	The body is dense and assumes Claude's competence (no basic-concept padding), but several boundary prohibitions recur across sections ('fail closed', 'never fabricate receipts', 'do not echo rejected values') and could be tightened without losing the protocol guarantees.	3 / 5
Actionability	Provides a copy-paste-ready bash runner-resolution block and an explicit ordered typed-MCP call sequence with named parameters and exact schema versions; minor gap is that tool-call bodies use '...' placeholders rather than literal filled examples.	4 / 5
Workflow Clarity	Steps 1-7 are clearly sequenced with explicit validation gates (preflight protocol-version check, re-plan on rejection, digest recompute-and-fail-closed, receipt verification) and feedback loops for a binding/execution operation.	5 / 5
Progressive Disclosure	Well-organized with descriptive headers and numbered steps in a single navigable file; no bundle files exist. At ~344 lines some receipt/model-policy detail could arguably split into a reference, but the workflow reads coherently inline.	4 / 5
	Total	16 / 20 Passed

Description

95%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, third-person description with explicit trigger tokens, a clear intent clause, and concrete domain framing. It cleanly answers both what and when with low conflict risk.

Dimension	Reasoning	Score
Specificity	Names the domain ('staff a durable goal from registered Local, owner Cloud, and public Hub agents or teams') plus several concrete constituents and behaviors (federated sourcing, per-turn staffing, goal-bound roster), but stops short of enumerating multiple distinct discrete actions.	4 / 5
Completeness	Explicitly answers both 'what' (staff a durable goal from registered agents/teams; host LLM staffs each turn) and 'when' ('Use when the user types ... mentions ... or asks ...') with concrete trigger phrases.	5 / 5
Trigger Term Quality	Comprehensive natural trigger coverage including exact invocation tokens ('$hephaestus-network, /hep-network, or /agentlas-network'), a mention trigger ('mentions @Hephaestus'), and a paraphrased intent trigger ('asks Agentlas to staff a durable goal').	5 / 5
Distinctiveness Conflict Risk	Tied to highly specific invocation tokens and the Agentlas/Hephaestus niche, giving it a clear trigger footprint with minimal overlap risk against other skills.	5 / 5
	Total	19 / 20 Passed

Validation

100%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: agentlas-ai/Agentlas-OS
Path: .agents/skills/hephaestus-network/SKILL.md
Commit: a7988bb

Reviewed: 4 days ago

Table of Contents

Discovery Implementation Validation

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.