Borrowing it
Nothing to install: this file belongs to AbdullahMalik17/Voice-Assistant17. 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/AbdullahMalik17/Voice-Assistant17/main/.claude/commands/sp.phr.mdgit clone --depth 1 https://github.com/AbdullahMalik17/Voice-Assistant17Wrote 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/abdullahmalik17/voice-assistant17/sp.phr)<a href="https://agentmods.dev/commands/abdullahmalik17/voice-assistant17/sp.phr"><img src="https://agentmods.dev/badge/commands/abdullahmalik17/voice-assistant17/sp.phr.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 | $0.00019 | $0.01853 |
| Opus 5 | $0.00010 | $0.00927 |
| Sonnet 5 | $0.00004 | $0.00371 |
| Haiku 4.5 | $0.00002 | $0.00185 |
Grade A, and why
sp.phr 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- sp.phr — 100% identical, 390 lines differ
How it starts
The opening of the file, as written. The whole thing — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.
COMMAND: Record this AI exchange as a structured PHR artifact
CONTEXT
The user has just completed work (or is requesting work) and needs to capture this exchange as a Prompt History Record (PHR) for:
- Learning and pattern recognition (spaced repetition)
- Team knowledge sharing and traceability
- Compliance and audit requirements
- Building a searchable corpus of effective prompts
User's input to record:
$ARGUMENTS
CRITICAL: The complete text above is the PROMPT to preserve verbatim. Do NOT truncate to first line only.
YOUR ROLE
Act as a meticulous documentation specialist with expertise in:
- Knowledge management and organizational learning
- Software development lifecycle documentation
- Metadata extraction and classification
- Creating structured, searchable technical records
QUICK OVERVIEW (strict)
After completing ANY work, automatically create a PHR:
- Detect work type: constitution|spec|plan|tasks|implementation|debugging|refactoring|discussion|general
- Generate title: 3-7 word descriptive title summarizing the work
- Capture context: COMPLETE conversation (never truncate to summaries)
- Route correctly:
- Pre-feature work →
history/prompts/ - Feature-specific work →
specs/<feature>/prompts/
- Pre-feature work →
- Confirm: Show "📝 PHR-NNNN recorded"
OUTPUT STRUCTURE (with quick flywheel hooks)
Execute this workflow in 5 sequential steps, reporting progress after each:
Step 1: Execute User's Request (if not already done)
If the user provided a task/question in $ARGUMENTS:
- Complete the requested work first
- Provide full response to user
- Then proceed to Step 2 to record the exchange
If you already completed work and user just wants to record it:
- Skip to Step 2
Step 2: Determine Stage and Routing
Select ONE stage that best describes the work:
Constitution (→ history/prompts/constitution/):
constitution- Defining quality standards, project principles
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 · 196 lines · 19 tokens per session scan A e9f0604bd0ed
sp.phr is a command published in the GitHub repository AbdullahMalik17/Voice-Assistant17 (11 stars, last pushed 2mo ago), licensed MIT. It adds 19 tokens to every session and 1,853 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 2026-08-30.
Other commands, from other repositories
minutes-ideas
Surface recent voice memos and ideas captured from any device. Use when the user asks "what ideas did I have?", "what were my recent memos?", "what did I record while walking?", or wants to recall a captured thought.
learn
Force claude-smart to extract learnings from this session now.
memory-store
Store an insight, decision, or pattern to memory.
cc-memory
Configure persistent memory that survives across sessions using a layered approach: split rule files for always-loaded context, auto-memory for organic learning, and optional MCP-backed long-term memory for large codebases.
analyze-context
USE WHEN you want to analyze project context before starting work on a task. Calls context + recall, then synthesizes goals, decisions, gotchas, and relevant memories into a pre-task brief.
lians-recall
Recall current (non-stale) facts from Lians memory, optionally as-of a past date.