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 skills add SerendipityOneInc/ZooData-Skills --skill amazon-competitor-intelligence-monitorgit clone --depth 1 https://github.com/SerendipityOneInc/ZooData-SkillsWrote 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/skills/serendipityoneinc/zoodata-skills/amazon-competitor-intelligence-monitor)<a href="https://agentmods.dev/skills/serendipityoneinc/zoodata-skills/amazon-competitor-intelligence-monitor"><img src="https://agentmods.dev/badge/skills/serendipityoneinc/zoodata-skills/amazon-competitor-intelligence-monitor/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/skills/serendipityoneinc/zoodata-skills/amazon-competitor-intelligence-monitor"><img src="https://agentmods.dev/badge/skills/serendipityoneinc/zoodata-skills/amazon-competitor-intelligence-monitor.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 | $0.00194 | $0.03851 |
| Opus 5.5 | $0.00078 | $0.01540 |
| Sonnet 5.5 | $0.00039 | $0.00770 |
| Haiku 4.5 | $0.00019 | $0.00385 |
Grade C, and why
amazon-competitor-intelligence-monitor scanned grade C with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
- **Working dir**: `WORK=$(mktemp -d)` (private, 0700 — not a predictable path); remove it with `rm -rf "$WORK"` after `review-aggregate` succeeds or the fallback aborts How it starts
The opening of the file, as written. The whole thing — 213 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ZooData — Competitor Intelligence Monitor
Know your enemy. Two modes: Full Scan + Quick Check. Respond in user's language.
Files
| File | Purpose |
|---|---|
{skill_base_dir}/scripts/zoodata.py |
Execute for all API calls (run --help for params) |
{skill_base_dir}/references/reference.md |
Load for exact field names or response structure |
{skill_base_dir}/monitor-data/ |
Runtime storage (auto-created): config.json, baseline.json, history/, alerts.json |
Credential
Required: ZOODATA_API_KEY. Get free key at zoodata.ai/api-keys.
Capabilities & Data Flow
- Network: only
https://api.zoodata.ai(BearerZOODATA_API_KEY). SettingZOODATA_BASE_URLto an untrusted host (anything other thanapi.zoodata.ai/*.zoodata.ai/ localhost) makes the CLI refuse the request and withhold the key — the Bearer token is never sent to an untrusted host. - Execution: bundled shared ZooData CLI
{skill_base_dir}/scripts/zoodata.py(Python 3, stdlib-only). This skill allowscategories,market,competitors,products,product,history,analyze,competitor-analysis,check, plus the review fallback toolkit (reviews-raw/review-tag-prompt/review-reduce-prompt/review-aggregate). Do not invoke unrelated subcommands for this skill's tasks — the bundled manifest{skill_base_dir}/scripts/allowed-commands.jsonenforces this: the CLI refuses out-of-scope subcommands with a structuredCOMMAND_NOT_ALLOWEDerror before any API request. - Local files: a private temporary working dir (created with
mktemp -d, removed when the fallback completes) during the review fallback; reads the optional credential store~/.zoodata/config.json. - Sent to the API: keywords, category paths, ASINs, marketplace/date and numeric filter values only. Never sent: budget, experience level, risk tolerance, or any other user-profile text — profile inputs map client-side to numeric filters.
- Credits: every API call consumes account credits. For broad or ambiguous requests, state the estimated credit cost and confirm with the user before running multi-call scans. The composite
competitor-analysiscommand executes ~17+ API calls (Full Scan, ~28-35 credits documented) in ONE invocation and has NO skip/trim flags — under a credit cap, use the granular commands instead.
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago Changed d3d725d52c9a
- 1mo ago First seen · 213 lines · 194 tokens per session scan C c791ebf8c253
amazon-competitor-intelligence-monitor is a skill published in the GitHub repository SerendipityOneInc/ZooData-Skills (77 stars, last pushed 6d ago), licensed MIT. It adds 194 tokens to every session and 3,851 once invoked, about $0.0008 per session on Opus 5.5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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