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 skills/erikdarlingdata/claude-plugins/query-plan-analysisnpx skills add erikdarlingdata/claude-plugins --skill query-plan-analysisgit clone --depth 1 https://github.com/erikdarlingdata/claude-pluginsWhat 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 | $0.00102 | $0.03554 |
| Opus 5 | $0.00051 | $0.01777 |
| Sonnet 5 | $0.00020 | $0.00711 |
| Haiku 4.5 | $0.00010 | $0.00355 |
Grade A, and why
query-plan-analysis 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 — 295 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reading a SQL Server execution plan
A query plan tells you what SQL Server decided to do and, if it's an actual plan, what happened when it did. Most bad plan analysis comes from confusing those two things, or from reaching for the most visually obvious number rather than the one that means something.
Work through the triage order below. It exists to establish ground truth before you form an opinion, because almost every wrong conclusion about a plan comes from forming the opinion first.
Step 0: extract the plan before you read it
Never read a .sqlplan file directly into context, and never grep one.
- They are large. A trivial two-table join runs 120 KB; real plans run into megabytes. Reading one wastes your context and you will still miss things, because the interesting attributes are scattered across thousands of lines.
- They are usually UTF-16, so
grep,rg, and friends silently match nothing. Finding noPlanAffectingConvertin a UTF-16 plan tells you nothing at all about whether the plan contains one. - Some plans lie about their own encoding: SSMS writes UTF-16, but a plan
that has been opened and re-saved is often UTF-8 bytes still declaring
encoding="utf-16". Strict XML parsers reject those.
Run the bundled extractor, which handles all of this and prints a digest ordered
to match the steps below. It lives at scripts/extract.py, in the same directory
as this file. Resolve that to an absolute path and call it with one — your
working directory is not the skill directory, and when this skill is installed as
a plugin the skill directory is not anywhere you can guess:
python <this-skill-dir>/scripts/extract.py /path/to/plan.sqlplan
It needs only the Python standard library. Add --top 20 to widen the ranked
sections on a large plan.
When you need more detail about one operator — its predicates, its seek keys, its per-thread numbers — do not open the raw XML. Ask the extractor:
python <this-skill-dir>/scripts/extract.py /path/to/plan.sqlplan --node 16
What ships with it
9 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.
- 2d ago First seen · 295 lines · 102 tokens per session scan A 7fc0cc9f3d08
query-plan-analysis is a skill published in the GitHub repository erikdarlingdata/claude-plugins (20 stars, last pushed 1mo ago), licensed MIT. It adds 102 tokens to every session and 3,554 once invoked, about $0.0005 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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