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blockrun

BlockRun works with Claude Code and Google Antigravity.

Quality

52%

Does it follow best practices?

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SecuritybySnyk

Medium

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tessl review fix ./skills/blockrun/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

71%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is a strong operational reference: concrete, executable SDK examples for every supported capability, clear decision tables for when to invoke BlockRun, and useful cost guidance. Its main weaknesses are redundancy (pricing and QR/setup code duplicated across sections) and the absence of any progressive disclosure — a dense API reference is inlined where a separate reference file would keep SKILL.md lean.

Suggestions

Consolidate the three pricing locations (Philosophy table, Available Models table, Cost Reference section) into a single cost table, and keep the wallet-setup and QR-code snippets in one place instead of repeating them in "Wallet & Balance" and "Setup & Funding".

Move the xAI Live Search parameter tables, source-type schemas, and detailed cost math into a references/live-search.md file, leaving SKILL.md as a lean overview with one-level-deep pointers.

Add a pre-call validation step in the setup flow (e.g., check get_balance() and warn before the first paid call when the balance is zero) to close the workflow's main checkpoint gap.

DimensionReasoningScore

Conciseness

The body is mostly efficient — it skips concept explanations and leads with concrete operational detail — but pricing is repeated in three places (the "Philosophy" table, the "Available Models" table, and the entire "Cost Reference" section), the QR-code snippet and wallet-setup code each appear twice verbatim, and "Example User Prompts" substantially restates "When to Use". The duplication goes beyond the "minor instances that could be trimmed" of the score-4 anchor, so it is not the level above.

3 / 5

Actionability

Every common case has copy-paste-ready executable Python: wallet setup, chat, live X search (simple and filtered), image generation, balance check, and budget tracking, plus pip install commands, parameter tables with defaults, and a troubleshooting section with concrete fixes. The score-4 anchor ("minor gaps") does not apply — no common case is left to inference.

5 / 5

Workflow Clarity

The setup flow is clearly sequenced (install SDK → setup_agent_wallet() → check balance → fund via QR) and the budget-control section includes an explicit validate-and-stop checkpoint loop. It falls short of 5 because there is no verification that the wallet is funded before making calls and no error-recovery loop beyond the static troubleshooting entries.

4 / 5

Progressive Disclosure

Sections are well organized with clear headers, but there are no bundle files at all — the full xAI Live Search parameter/source-type reference and the cost tables are inlined in a ~285-line SKILL.md where they clearly belong in a separate one-level-deep reference file. This matches "content that should be separate is inline"; it is above score 2 because the inline structure is genuinely well-signaled and navigable.

3 / 5

Total

15

/

20

Passed

Description

11%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is a bare product tagline: it names BlockRun and two host platforms but states zero capabilities and zero usage triggers. A user (or Claude) reading only this line could never decide when to invoke the skill. It fails all four dimensions of a functional skill description.

Suggestions

State the concrete capabilities in the description, e.g. "Generates images (DALL-E 3, Nano Banana), fetches real-time X/Twitter data via Grok Live Search, and routes requests to external LLMs (GPT-5.2, DeepSeek) using x402 micropayments from a USDC wallet."

Add an explicit trigger clause: "Use when the user asks to generate images, check what's trending on X, wants a second opinion from another LLM, or asks to check their BlockRun wallet balance."

Include the natural user vocabulary (image, logo, X/Twitter, trending, second opinion, wallet balance) so the description matches what users actually say.

DimensionReasoningScore

Specificity

The description's only statement is "BlockRun works with Claude Code and Google Antigravity." — no concrete action beyond the generic "works with" is named (no image generation, X data, LLM routing, or payment capability), matching the anchor for entirely vague with no concrete actions; even the score-2 anchor requires a minimal generic action verb like "Processes", which is absent.

1 / 5

Completeness

Neither "what" (no capability is described at all) nor "when" (no "Use when..." clause or equivalent trigger guidance) is present, so it matches the lowest anchor of both missing; the "missing Use-when caps completeness at 3" guideline is moot because the "what" half is also absent.

1 / 5

Trigger Term Quality

It contains product names ("BlockRun", "Claude Code", "Google Antigravity") but none of the natural phrases a user would say when needing the skill's capabilities (image, X/Twitter, live data, second opinion, wallet), matching "one or two generic keywords; missing the natural phrases users say" rather than the jargon-free, capability-rich coverage of higher anchors.

2 / 5

Distinctiveness Conflict Risk

Naming a unique product ("BlockRun") gives it a nominal identity, but with no functional niche stated it reads as a generic integration claim that could overlap with any tool-integration skill and cannot trigger on the right task, matching "very broad; high overlap risk" rather than the clearly-carved niche of score 5.

2 / 5

Total

6

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository

administrakt0r/AI-Agents-Safe-Coding-Skills

Path

skills/blockrun/SKILL.md

Reviewed

Table of Contents

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