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/TheLobbi/claudeWrote 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/thelobbi/claude/edge)<a href="https://agentmods.dev/commands/thelobbi/claude/edge"><img src="https://agentmods.dev/badge/commands/thelobbi/claude/edge/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/commands/thelobbi/claude/edge"><img src="https://agentmods.dev/badge/commands/thelobbi/claude/edge.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 | $0.00021 | $0.04903 |
| Opus 5.5 | $0.00008 | $0.01961 |
| Sonnet 5.5 | $0.00004 | $0.00981 |
| Haiku 4.5 | $0.00002 | $0.00490 |
Grade A, and why
lg:edge 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 1mo 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 — 877 lines — stays where its author put it; the contents beside it link to each section on GitHub.
lg:edge - Edge Management
Manage edges (connections) between nodes in LangGraph graphs including regular edges, conditional edges, and dynamic routing.
Workflow Steps
Add Regular Edge
-
Validate Nodes
- Check source node exists
- Check target node exists
- Verify compatible state schemas
-
Create Edge
- Add edge to graph definition
- Update routing logic
- Add to graph compilation
-
Update Tests
- Add edge test
- Update integration tests
-
Update Documentation
- Update graph diagram
- Document flow
Add Conditional Edge
-
Validate Configuration
- Check source node exists
- Check target nodes exist
- Validate condition function
-
Generate Condition Function
- Create routing logic
- Add condition checks
- Handle default case
-
Add Conditional Edge
- Add to graph definition
- Configure routing map
- Add error handling
-
Update Tests
- Test all routing paths
- Test edge cases
- Test default routing
-
Update Documentation
- Document routing logic
- Add decision tree diagram
Remove Edge
-
Identify Edge
- Find edge in graph
- Check for dependencies
-
Remove Edge
- Remove from graph definition
- Clean up routing logic
- Remove condition function (if orphaned)
-
Update Tests
- Remove edge tests
- Update integration tests
-
Update Documentation
- Update graph diagram
Edge Types
Regular Edge
Simple one-way connection.
graph.add_edge("node_a", "node_b")
Flow:
node_a → node_b
Conditional Edge
Branch based on condition.
def route_condition(state: State) -> str:
"""Determine next node based on state."""
if state["score"] > 0.8:
return "high_score_path"
elif state["score"] > 0.5:
return "medium_score_path"
else:
return "low_score_path"
graph.add_conditional_edges(
"node_a",
route_condition,
{
"high_score_path": "node_b",
"medium_score_path": "node_c",
"low_score_path": "node_d"
}
)
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.
- 1mo ago First seen · 877 lines · 21 tokens per session scan A c1311707e4b8
lg:edge is a command published in the GitHub repository TheLobbi/claude (21 stars, last pushed 6d ago), licensed MIT. It adds 21 tokens to every session and 4,903 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-05.
Other commands, from other repositories
verify
Grade work that already exists and decide whether it can merge. Runs the project's current unit, integration, and E2E suites plus security scanning and type checking, scores every dimension 0-10, and returns a merge verdict with a VERIFIED-vs-CLAIMED evidence manifest. Writes no test files and edits no source. Use…
cover
Generate tests that do not exist yet. Analyzes coverage gaps, then writes and runs new test files across three tiers (unit, integration via testcontainers, Playwright E2E), one test-generator agent per tier, healing failures for up to 3 iterations. Use when code has no tests or when raising coverage after…
session
Complete guide to managing pair programming sessions.
test-tdd
Run when user calls /test-tdd. Scans modified files, locates their corresponding unit/integration test suites, and runs them.
kill-mutants
Analyze surviving mutants from a mutation testing run and write targeted unit tests to kill them. Re-runs mutations to confirm kills.
story-and-test
For the component(s) in scope.