remindb: Skill for Claude Code

.claude/skills/add-bench-scenario/SKILL.md

add-bench-scenario is a skill for Claude Code from radimsem/remindb. It costs 106 tokens per session (1,710 once invoked), scanned A, original, MIT.

A recipe for adding a scenario to remindb’s benchmark suite, which measures how much text an agent needs to complete a task using remindb compared with ordinary shell tools such as grep, cat, and find.

In plain words
What is it for?
Use it to add a scenario function, connect it to the benchmark runner, and optionally add command-line flags. The result reports the token counts and savings for both approaches.
Why use it?
It keeps new benchmark cases consistent and ensures they are included in the command that runs the full comparison. This avoids adding a test that exists in code but is never measured.

Skill for Claude Code

Written for Claude Code: installed under .claude/. Also seen: reads .claude/ paths.

This is radimsem/remindb's own configuration. It tells Claude Code how to work on remindb itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything remindb configures →

Reuse

Borrowing it

Nothing to install: this file belongs to radimsem/remindb. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/radimsem/remindb/dev/.claude/skills/add-bench-scenario/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/radimsem/remindb

Made for: Claude Code.

Wrote 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.

agentmods badge for add-bench-scenario

README.md
[![agentmods](https://agentmods.dev/badge/skills/radimsem/remindb/add-bench-scenario.svg)](https://agentmods.dev/skills/radimsem/remindb/add-bench-scenario)
Your own site
<a href="https://agentmods.dev/skills/radimsem/remindb/add-bench-scenario"><img src="https://agentmods.dev/badge/skills/radimsem/remindb/add-bench-scenario.svg" alt="Measured on agentmods" height="20"></a>
Per session 106 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,710 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Agent Snooping · line 118
    Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.
    Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00106 $0.01710
Opus 5 $0.00053 $0.00855
Sonnet 5 $0.00021 $0.00342
Haiku 4.5 $0.00011 $0.00171

Measured 8d ago against content hash fa8a970170a6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

add-bench-scenario 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 8d 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.

.claude/skills/add-bench-scenario/SKILL.md · 120 lines

How it starts

The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Add a benchmark scenario

internal/bench/ is remindb's external-facing benchmark — it compares "how many tokens does an agent consume to do X via remindb tools" against "how many would they consume doing X with grep / cat / find". The output is a token-savings table rendered via text/tabwriter. It's invoked from the remindb bench CLI subcommand and exercised end-to-end by scripts/bench-agents.sh.

This is not the Go testing.B benchmark surface — those live as Benchmark* functions inside pkg/*/bench_test.go and have their own discipline.

Where it lands

Two files for a typical scenario, three if it needs CLI flag plumbing.

File What changes
internal/bench/scenarios.go New benchXxx(ctx, session, srcDir, ...) (scenarioResult, error) function
internal/bench/bench.go Wire the new scenario into Run, append to results
cmd/remindb/... (only if new flag needed) Surface a new flag on the bench subcommand and pass it into bench.Config

The scenario function shape

Every scenario implements the same contract: produce one (or more) scenarioResult{name, naiveTok, remindbTok} by measuring two paths to the same answer — the naive path (token count of what an agent would have to read using shell tools) and the remindb path (token count of the tool's response).

Mirror benchTree, benchSearch, or benchFetch in scenarios.go:

func benchExample(ctx context.Context, s *gomcp.ClientSession, srcDir string, budget int) (scenarioResult, error) {
    // Naive path: what the agent would read using shell tools.
    naive := tokens.Estimate(naiveContent(srcDir))

    // remindb path: call the tool and count its response.
    text, err := callTool(ctx, s, "MemoryExample", map[string]any{
        "budget": budget,
    })
    if err != nil {
        return scenarioResult{}, err
    }

    return scenarioResult{
        name:       "example",
        naiveTok:   naive,
        remindbTok: tokens.Estimate(text),
    }, nil
}

Read the full file on GitHub · 120 lines

Changes

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.

  1. 8d ago First seen · 120 lines · 106 tokens per session scan A fa8a970170a6

Subscribe to this mod's changes

add-bench-scenario is a skill published in the GitHub repository radimsem/remindb (125 stars, last pushed 1mo ago), licensed MIT. It adds 106 tokens to every session and 1,710 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.