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/techgangboss/agentstore/browsegit clone --depth 1 https://github.com/techgangboss/agentstoreWrote 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/techgangboss/agentstore/browse)<a href="https://agentmods.dev/commands/techgangboss/agentstore/browse"><img src="https://agentmods.dev/badge/commands/techgangboss/agentstore/browse.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 | $0.00009 | $0.00418 |
| Opus 5 | $0.00005 | $0.00209 |
| Sonnet 5 | $0.00002 | $0.00084 |
| Haiku 4.5 | $0.00001 | $0.00042 |
Grade A, and why
browse scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Browse AgentStore Marketplace
Search and browse available agents in the AgentStore marketplace.
Instructions
-
Use WebFetch to call the AgentStore API:
GET https://api.agentstore.tools/api/agentsAdd query params if provided:
?search={query}&tag={category} -
Parse the JSON response and display agents in a clean format
-
For each agent show:
- Name and version
- Publisher name
- Description (truncated to ~100 chars)
- Type: "Open Source" or "Proprietary"
- Price: "FREE" or "$X.XX"
- Tags as badges
-
After listing, ask if user wants to:
- See details for a specific agent
- Install an agent with
/install-agent {agent_id} - Filter by different category
Display Format
## AgentStore Marketplace
### {name} v{version}
by {publisher} | {type}
{description}
**Price:** {FREE or $X.XX} | **Tags:** {tags}
---
Example Output
## AgentStore Marketplace
### Code Reviewer v1.0.0
by TechGang Boss | Open Source
AI-powered code review agent that analyzes your code for bugs and security issues.
**Price:** FREE | **Tags:** code-quality, productivity
---
### SQL Expert v1.0.0
by TechGang Boss | Proprietary
Expert SQL agent that writes optimized queries and explains execution plans.
**Price:** $5.00 | **Tags:** database, productivity
---
Found 2 agents. Use `/install-agent {agent_id}` to install.
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.
- 3d ago First seen · 73 lines · 9 tokens per session scan A 14b470a86d1e
browse is a command published in the GitHub repository techgangboss/agentstore (4 stars, last pushed 6mo ago), licensed MIT. It adds 9 tokens to every session and 418 once invoked, about $0.0000 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 2026-08-31.
Other commands, from other repositories
git
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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.