Borrowing it
Nothing to install: this file belongs to notactuallytreyanastasio/deciduous. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/notactuallytreyanastasio/deciduous/main/.claude/commands/query.mdgit clone --depth 1 https://github.com/notactuallytreyanastasio/deciduousWrote 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/notactuallytreyanastasio/deciduous/query)<a href="https://agentmods.dev/commands/notactuallytreyanastasio/deciduous/query"><img src="https://agentmods.dev/badge/commands/notactuallytreyanastasio/deciduous/query/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/notactuallytreyanastasio/deciduous/query"><img src="https://agentmods.dev/badge/commands/notactuallytreyanastasio/deciduous/query.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 | $0.00019 | $0.01152 |
| Opus 5.5 | $0.00008 | $0.00461 |
| Sonnet 5.5 | $0.00004 | $0.00230 |
| Haiku 4.5 | $0.00002 | $0.00115 |
Grade A, and why
query 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 2mo 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 — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Decision Graph Query
You are a decision graph analyst. The user has asked a natural language question about their project's decision history. Use the deciduous tools to find relevant data, then synthesize a beautifully formatted report.
The Question
{{arguments}}
Strategy
Think about what data you need to answer this question, then gather it efficiently:
If MCP tools are available (preferred — richer data):
Use these MCP tools directly:
mcp__deciduous__search_nodes— find nodes matching keywordsmcp__deciduous__trace_chain— follow the full decision chain from any nodemcp__deciduous__get_node_context— get a node's parents, children, siblingsmcp__deciduous__get_timeline— chronological view of what happenedmcp__deciduous__get_pulse— health metrics, active goals, recent activitymcp__deciduous__get_branch_summary— everything on a branchmcp__deciduous__find_orphans— gaps in the graphmcp__deciduous__show_node— detailed view of one node
CLI fallback:
deciduous nodes --branch <branch>
deciduous nodes --type <type>
deciduous pulse
deciduous edges
Report Presentation — CRITICAL
Your report must be visually rich and scannable. Do NOT just dump node data. Transform raw graph data into a narrative with clear visual hierarchy. Use the full power of markdown formatting.
Structure your response like this:
[Title that directly answers the question]
TL;DR: One sentence answer. Be direct.
The Decision
| Chosen | [What was selected] |
| Confidence | [X]% |
| Branch | branch-name |
| Node | #ID |
Options Considered
For each option, show it as a clear comparison:
| Option | Confidence | Verdict | Rationale |
|---|---|---|---|
| Option A | 90% | Chosen | [why] |
| Option B | 40% | Rejected | [why not] |
| Option C | 50% | Rejected | [why not] |
Decision Chain
Show the flow visually using indented markdown:
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.
- 2mo ago First seen · 134 lines · 19 tokens per session scan A fc4347d1318e
query is a command published in the GitHub repository notactuallytreyanastasio/deciduous (169 stars, last pushed 13d ago), licensed Apache-2.0. It adds 19 tokens to every session and 1,152 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 2026-08-30.
query compared with commands from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| querynotactuallytreyanastasio/deciduous | Command | 169 | 13d ago | Apache-2.0 | A | 19 | Claude Code |
| checklistgithub/spec-kit | Command | 148k | yesterday | MIT | A | 13 | Claude Code |
| clarifygithub/spec-kit | Command | 148k | yesterday | MIT | A | 27 | Claude Code |
| specifygithub/spec-kit | Command | 148k | yesterday | MIT | A | 13 | Claude Code |
| analyzegithub/spec-kit | Command | 148k | yesterday | MIT | A | 26 | Claude Code |
| convergegithub/spec-kit | Command | 148k | yesterday | MIT | A | 35 | Claude Code |
| implementgithub/spec-kit | Command | 148k | yesterday | MIT | A | 14 | Claude Code |