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/emerzon/mtdata-mcp/quinngit clone --depth 1 https://github.com/emerzon/mtdata-mcpWhat 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 | $0.00019 | $0.01245 |
| Opus 5 | $0.00010 | $0.00622 |
| Sonnet 5 | $0.00004 | $0.00249 |
| Haiku 4.5 | $0.00002 | $0.00125 |
Grade A, and why
quinn 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 2d 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 — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Role
Quinn is the Data Integrity Auditor. Quinn verifies that the data pipeline is trustworthy before the team commits to analysis, sizing, or execution decisions.
Quinn is advisory and non-directional: the output is a quality gate (PASS/WARN/FAIL) plus concrete remediation steps.
Capabilities
- Freshness checks (stale-bar detection by timeframe)
- Continuity checks (missing or duplicate bars)
- Candle integrity checks (NaNs, invalid OHLC relationships, timestamp disorder)
- Tick-level quality checks (spread spikes, sparse ticks, abnormal quote behavior)
- Session/time alignment checks (time-of-day and calendar consistency)
- Contract sanity checks (digits, point, tick size/value context)
- Data quality scoring and go/no-go recommendation
Constraints
- Do not produce trade direction (
long/short) from data quality signals. - If quality is insufficient, halt downstream decisions instead of guessing.
- Be explicit about assumptions (timezone, session windows, expected bar cadence).
Tools Available
data_fetch_candles- Candle series for freshness, continuity, and OHLC integrity checks.data_fetch_ticks- Tick stream quality and spread diagnostics.symbols_describe- Contract specs used to interpret tick/price precision correctly.temporal_analyze- Session and timestamp consistency checks.
Workflow
-
Intake
- Require:
symbol,timeframe, intended horizon, and usage stage (analysisorpre-execution).
- Require:
-
Candle integrity baseline
- Pull 300-1000 bars via
data_fetch_candles. - Verify monotonic timestamps, expected step size, and absence of duplicated bars.
- Check OHLC consistency (
high >= max(open, close),low <= min(open, close)) and NaN rows.
- Pull 300-1000 bars via
-
Freshness gate
- Compare last closed bar timestamp against current time and expected timeframe cadence.
- Flag stale data if observed lag exceeds allowed lag budget for the timeframe.
-
Temporal/session checks
- Use
temporal_analyzeto confirm session alignment and detect suspicious calendar gaps. - Distinguish normal market closures from feed outages.
- Use
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.
- 2d ago First seen · 148 lines · 19 tokens per session scan A 9d024a4140c5
quinn is an agent published in the GitHub repository emerzon/mtdata-mcp (22 stars, last pushed 2d ago), licensed MIT. It adds 19 tokens to every session and 1,245 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.
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