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/vijayjoshi24/ea-agent-skillsWrote 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/vijayjoshi24/ea-agent-skills/decide)<a href="https://agentmods.dev/commands/vijayjoshi24/ea-agent-skills/decide"><img src="https://agentmods.dev/badge/commands/vijayjoshi24/ea-agent-skills/decide.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 | $0.00000 | $0.00356 |
| Opus 5 | $0.00000 | $0.00178 |
| Sonnet 5 | $0.00000 | $0.00071 |
| Haiku 4.5 | $0.00000 | $0.00036 |
Grade A, and why
decide 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 8d 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.
What it actually says
/decide
Capture an architectural decision as a formal ADR (Architecture Decision Record).
When to use
Any time a significant design choice is made — technology selection, pattern adoption, build-vs-buy, integration approach, platform strategy. Decisions not documented are decisions that will be re-litigated.
What it produces
- A complete ADR in standard format: Title, Status, Context, Decision, Consequences
- Optional: trade-off comparison table across the evaluated options
- Optional: link map to related ADRs (supersedes / superseded-by)
How to invoke
/decide
Then describe the decision. Examples:
/decide
We're choosing between Azure Service Bus and Kafka for our event backbone.
The system needs to handle 50k events/day, we're an Azure-native shop,
and the team has limited Kafka ops experience.
/decide
We've decided to adopt the Strangler Fig pattern to migrate our monolith.
Capture the rationale, alternatives we considered, and the consequences.
Output format
# ADR-{NNN}: {Title}
**Date:** {date}
**Status:** Proposed | Accepted | Deprecated | Superseded
**Deciders:** {who made this decision}
## Context
{What forces are at play? What problem are we solving?}
## Decision
{What was decided, in active voice: "We will..."}
## Options considered
| Option | Pros | Cons | Fit |
|--------|------|------|-----|
## Consequences
### Positive
### Negative
### Risks and mitigations
## Related decisions
Activates skill
skills/adr-writer/
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.
- 8d ago First seen · 65 lines · 0 tokens per session scan A b618de6be4b5
decide is a command published in the GitHub repository vijayjoshi24/ea-agent-skills (5 stars, last pushed 4mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 356 tokens. 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
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.