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/vvedantb/eva/changeloggit clone --depth 1 https://github.com/vvedantb/evaWrote 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/vvedantb/eva/changelog)<a href="https://agentmods.dev/commands/vvedantb/eva/changelog"><img src="https://agentmods.dev/badge/commands/vvedantb/eva/changelog.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 | $0.00000 | $0.00197 |
| Opus 5 | $0.00000 | $0.00098 |
| Sonnet 5 | $0.00000 | $0.00039 |
| Haiku 4.5 | $0.00000 | $0.00020 |
Grade A, and why
changelog 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.
What it actually says
Review all changes made in this conversation and add a new entry to internal/changelog/<YYYY-MM>.md — the file for today's month. If that file does not exist yet, create it with a # Changelog — <Month YYYY> heading (e.g. # Changelog — September 2026) followed by a blank line.
Format: ## <Title> - <YYYY-MM-DD> followed by bullet points describing each change.
Rules:
- Only add entries for medium-to-large changes/features, not quick fixes or bug fixes
- Each bullet should describe what changed and why, not implementation details
- Keep bullets concise (one line each)
- Add the new entry at the top of the month file, right after the
# Changelog — <Month YYYY>heading - Use today's date
- If multiple features were implemented, group them under one entry if related, or create separate entries if unrelated
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 Changed b1f0834972f7
- 4d ago First seen · 17 lines · 0 tokens per session scan A fa33921f12aa
changelog is a command published in the GitHub repository vvedantb/eva (101 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 197 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 2026-08-30.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
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.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
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.