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 ericrisco/rsc-harness --skill dynamodbgit clone --depth 1 https://github.com/ericrisco/rsc-harnessWrote 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/ericrisco/rsc-harness/dynamodb)<a href="https://agentmods.dev/skills/ericrisco/rsc-harness/dynamodb"><img src="https://agentmods.dev/badge/skills/ericrisco/rsc-harness/dynamodb/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/ericrisco/rsc-harness/dynamodb"><img src="https://agentmods.dev/badge/skills/ericrisco/rsc-harness/dynamodb.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00082 | $0.03088 |
| Opus 5.5 | $0.00033 | $0.01235 |
| Sonnet 5.5 | $0.00016 | $0.00618 |
| Haiku 4.5 | $0.00008 | $0.00309 |
Grade A, and why
dynamodb 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 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.
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 — 205 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DynamoDB — access-pattern-first modeling and capacity
DynamoDB is not a relational database with a different syntax. It has no joins, no ad-hoc queries, no
server-side aggregation, and it punishes schema changes after launch. So the modeling discipline IS the
work: enumerate every read and write the app must perform, THEN design keys so each one is a single
GetItem or Query. Add an index only when the base table physically cannot serve a pattern. Decide
capacity last.
Your job here is to stop the user from treating DynamoDB like SQL.
What you produce / what you refuse
You deliver three artifacts, in this order:
- An access-pattern list — a table of every query and write, with key condition, read/write, frequency, and what serves it. This is the contract the keys must satisfy.
- A key-design document — entity → PK/SK encoding → which table or named GSI serves each pattern.
- A capacity + cost recommendation — on-demand vs provisioned vs reserved, and the hot-partition risk.
You refuse to: click through the AWS console, wire the IaC/CI provisioning pipeline (that is
../deployment/SKILL.md), or model the data as normalized tables you then "join" in application code.
You emit DDL, IaC snippets, and example SDK calls — you do not provision the infrastructure.
The steps below run in sequence — access patterns, then keys, then indexes, then capacity. Reordering them is the single most common DynamoDB mistake.
Step 1 — Enumerate access patterns
You cannot query what your keys do not express, and there is no WHERE over arbitrary columns, so
produce this table before you name a single attribute. It is also exactly what scripts/verify.sh
checks: run scripts/verify.sh <path-to-key-design.{md,json}> and every row must carry a key target
(pk/sk or a named gsi) and a query_type. It FAILS on any pattern served by Scan, WARNS on
FilterExpression, and asserts ≤20 GSIs / ≤5 LSIs. Read-only; exits 0 on an empty or clean target.
What ships with it
5 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 First seen · 205 lines · 82 tokens per session scan A edbecfeeeef9
dynamodb is a skill published in the GitHub repository ericrisco/rsc-harness (231 stars, last pushed today), licensed MIT. It adds 82 tokens to every session and 3,088 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-09-03.
Other skills, from other repositories
nosql-database-design
Designs a NoSQL data model by leading with access pattern analysis. Covers DynamoDB single-table design (PK/SK/GSI) and MongoDB embedding vs referencing, consistency models, and capacity planning. Invoked when the user asks to design a DynamoDB schema, MongoDB data model, or NoSQL data model.
traverse-multi-hop
Expresses a multi-hop lineage question as a single variable-length path match against native graph storage, bounded by an explicit hop depth and an explicit relationship-type allowlist, instead of a recursive relational join that grows one level per hop.
transact-graph-write
Wraps every write to a shared graph edge in a transaction tied to the exact row version it was computed against, and retries a rejected write against the row's current state instead of dropping it or blindly reapplying stale values.
attach-receipts
Attaches sourcedoc/extractionrunid/schemaversion receipts to every edge at write time, and refuses to write any edge missing one of the three.
query-graph
Loads schema.sql into a local SQLite file, then answers availability and provenance questions against the nodes/edges tables with real SQL instead of re-reading source material.
score-and-merge
Scores candidate merge pairs on weighted signals and auto-merges only pairs clearing a stated threshold, routing the rest to a review queue with their score and signal breakdown attached.