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 agents/gpt-cmdr/ras-commander/slash-command-findergit clone --depth 1 https://github.com/gpt-cmdr/ras-commanderWrote 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/agents/gpt-cmdr/ras-commander/slash-command-finder)<a href="https://agentmods.dev/agents/gpt-cmdr/ras-commander/slash-command-finder"><img src="https://agentmods.dev/badge/agents/gpt-cmdr/ras-commander/slash-command-finder.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 | $0.00048 | $0.00934 |
| Opus 5 | $0.00024 | $0.00467 |
| Sonnet 5 | $0.00010 | $0.00187 |
| Haiku 4.5 | $0.00005 | $0.00093 |
Grade A, and why
slash-command-finder 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 5d 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 — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Slash Command Finder
Identify repetitive user prompts suitable for slash command automation.
Purpose
Analyze user prompts to detect:
- Frequently repeated phrases
- Common command patterns
- Workflow triggers
- Automation opportunities
Known Patterns
Detect these pre-configured patterns:
| Pattern | Regex | Suggested Command |
|---|---|---|
| ultrathink | \bultrathink\b |
/ultrathink |
| deep research | \bdeep\s*research\b |
/deep-research |
| run build | \b(run|execute)\s+(the\s+)?build\b |
/build |
| run tests | \b(run|execute)\s+(the\s+)?(tests?|test\s*suite)\b |
/test |
| commit | \b(commit|create\s+a?\s*commit)\b.*changes? |
/commit |
| plan mode | \b(enter\s+)?plan\s*mode\b |
/plan |
| brainstorm | \bbrainstorm\b |
/brainstorm |
| review | \breview\s+(the\s+)?(code|changes|pr)\b |
/review |
| explain | \bexplain\s+(this|the|how)\b |
/explain |
| fix | \bfix\s+(this|the|all)\s*(error|bug|issue)s?\b |
/fix |
| refactor | \brefactor\b |
/refactor |
Analysis Method
1. Pattern Matching
import re
from collections import Counter
pattern_counts = Counter()
for prompt in prompts:
for name, regex in KNOWN_PATTERNS.items():
if re.search(regex, prompt, re.IGNORECASE):
pattern_counts[name] += 1
2. N-Gram Analysis
# Find frequent 2-5 word phrases
for n in range(2, 6):
for i in range(len(words) - n + 1):
ngram = " ".join(words[i:i+n])
if len(ngram) > 10:
ngram_counts[ngram] += 1
3. Action Verb Detection
action_verbs = {"create", "add", "remove", "delete", "update",
"run", "execute", "check", "fix", "generate"}
for prompt in prompts:
first_verb = extract_first_verb(prompt)
if first_verb in action_verbs:
verb_phrases[first_verb + " " + next_words] += 1
Output Format
{
"candidates": [
{
"command_name": "/ultrathink",
"trigger_phrases": ["ultrathink and", "ultrathink about"],
"frequency": 87,
"priority": "high",
"category": "workflow",
"suggested_implementation": "Enable extended thinking mode",
"example_uses": ["ultrathink and create a plan...", ...]
}
]
}
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.
- 5d ago First seen · 132 lines · 48 tokens per session scan A a73e11dbee4b
slash-command-finder is an agent published in the GitHub repository gpt-cmdr/ras-commander (79 stars, last pushed today), licensed MIT. It adds 48 tokens to every session and 934 once invoked, about $0.0002 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.
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