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/sabbour/agentweaver/initgit clone --depth 1 https://github.com/sabbour/agentweaverWhat 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 | $0.00012 | $0.01090 |
| Opus 5 | $0.00006 | $0.00545 |
| Sonnet 5 | $0.00002 | $0.00218 |
| Haiku 4.5 | $0.00001 | $0.00109 |
Grade A, and why
init 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 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.
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 — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Squad Bridge: Init
Read the implementation plan and bootstrap a Squad team tailored to its
technology stack, architecture layers, and implementation phases. Run this
once after your initial /speckit.plan to get a squad that mirrors your
project's concrete technical shape.
Why plan and not spec? The spec (spec.md) is intentionally tech-agnostic
— it captures goals, users, and constraints. The plan (plan.md) is where
concrete technology decisions live (e.g., "React 19 with Next.js", "Go API
with gin"). Generating agents from the plan produces sharper charters with
accurate capabilities and routing rules.
Prerequisites
Verify Squad CLI is available:
squad --version
If that fails, install it first:
npm install -g @bradygaster/squad-cli
User Input
$ARGUMENTS
Steps
-
Read the plan from the active spec directory under
specs/(e.g.,specs/001-<name>/plan.md). If no plan exists, tell the user to run/speckit.planfirst and stop. Also readspec.mdfor supplementary context (goals, constraints, non-functional requirements). -
Read tasks from
specs/<id>/tasks.mdif it exists (used to infer work types and routing signals). -
Load bridge config from
.specify/extensions/squad/squad-config.ymlif it exists, otherwise use extension defaults. -
Analyze the plan to extract:
- Technology stack explicitly chosen (e.g., "React 19 with Next.js", "Go microservices with gin", "PostgreSQL with Prisma ORM")
- Architecture layers (frontend, backend, API gateway, data layer, infra)
- Implementation phases (if the plan defines phased delivery)
- Cross-cutting concerns (e.g., auth, testing, documentation, CI/CD)
- Any explicit roles or team structure mentioned in the plan or spec
-
Initialize Squad if
.squad/does not already exist:squad init -
Generate agent definitions — for each identified domain/concern, create a Squad agent with:
- A descriptive
name(e.g.,backend-engineer,frontend-engineer) - A
rolederived from the domain capabilitiesarray (name + level: expert/proficient/basic) inferred from how prominently the domain features in the planmodelset to the tier from config that matches the agent's complexitystatus: active
- A descriptive
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 · 117 lines · 12 tokens per session scan A 920ce5321884
init is a command published in the GitHub repository sabbour/agentweaver (5 stars, last pushed yesterday), licensed MIT. It adds 12 tokens to every session and 1,090 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 2026-08-31.
Other commands, from other repositories
send
Send a message to a running agent session. Use this to correct or direct a live agent mid-stream without killing and respawning it.
dispatcher
Pick the next-best repo to work on across the portfolio — rank free repos, recommend one, claim its lease atomically, and route to the entry command.
journey-audit
Outside-in product audit as a deep session — 7 read-only roles check what the site promises against what the code does, what a user experiences, what arrives by mail, and what the data says is used. Writes a dossier; needs a per-repo journey-manifest.
cost-tracker
Track session costs, understand token spend, and get optimization tips.
create_worktree
description: Create worktree and launch implementation session for a plan.
board
Show your job-application tracker board (grouped by status), or update an application's status.