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 seed-forge/harness-ai-kit --skill public-mongodb-expert-basegit clone --depth 1 https://github.com/seed-forge/harness-ai-kitWrote 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/seed-forge/harness-ai-kit/public-mongodb-expert-base)<a href="https://agentmods.dev/skills/seed-forge/harness-ai-kit/public-mongodb-expert-base"><img src="https://agentmods.dev/badge/skills/seed-forge/harness-ai-kit/public-mongodb-expert-base/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/seed-forge/harness-ai-kit/public-mongodb-expert-base"><img src="https://agentmods.dev/badge/skills/seed-forge/harness-ai-kit/public-mongodb-expert-base.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 | $0.00044 | $0.00733 |
| Opus 5 | $0.00022 | $0.00367 |
| Sonnet 5 | $0.00009 | $0.00147 |
| Haiku 4.5 | $0.00004 | $0.00073 |
Grade A, and why
public-mongodb-expert-base 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 10d 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 — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MongoDB Knowledge Base
Foundational guidance for building applications with MongoDB.
Source: Adapted from mongodb/agent-skills (schema-design + query-optimizer + connection).
Document Model
- Design documents around access patterns, not normalization.
- Embed related data that's always read together (1:1, 1:few).
- Reference (DBRef or manual ID) for data that grows unbounded or is accessed independently.
- Use arrays for ordered collections; use sub-documents for named fields.
- Avoid anti-patterns: unbounded arrays, massive documents (>16MB), excessive nesting.
Schema Design Patterns
| Pattern | Use for |
|---|---|
| Embedding | 1:1, 1:few relationships, always-read-together data |
| Referencing | 1:many (unbounded), independent access |
| Bucket | Time-series data (group by time window) |
| Tree | Hierarchical data (materialized paths, nested sets) |
| Outlier | Handle occasional large documents separately |
| Extended Reference | Embed frequently accessed fields, reference the rest |
Indexing
- Index fields used in queries, sorts, and aggregation
$match/$sortstages. - Compound index order matters: equality first, then range, then sort.
- Use
explain()to verify index usage (look forIXSCAN, avoidCOLLSCAN). - Text indexes for full-text search; 2dsphere for geospatial queries.
- TTL indexes for auto-expiring documents.
- Monitor with
$indexStats— drop unused indexes.
Aggregation Pipeline
- Order stages for efficiency:
$matchand$sortfirst (use indexes). $lookupfor joins (prefer embedding when possible).$groupfor aggregation;$unwindto flatten arrays before grouping.- Use
$projectearly to reduce document size through the pipeline. $facetfor multiple aggregations in one query.
Connection & Configuration
- Connection string:
mongodb://host:port/db?options - Use connection pooling (built into all official drivers).
- Set
w=majorityfor write concern (durability). - Set
readPreference=secondaryPreferredfor read scaling. - Use
retryWrites=trueandretryReads=true.
What ships with it
3 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.
- 10d ago First seen · 69 lines · 44 tokens per session scan A a5628e9072da
public-mongodb-expert-base is a skill published in the GitHub repository seed-forge/harness-ai-kit (22 stars, last pushed 9d ago), licensed Apache-2.0. It adds 44 tokens to every session and 733 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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