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accint-solve

Route a goal through acc's scored-memory loop via acc_act(runtime="solve"); deliberate any returned brain_frame and submit via continue.

40

Quality

37%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

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tessl review fix ./skills/accint-solve/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

71%Scale 1-5

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

This is a concise routing skill that clearly sequences the MCP verb calls and handles the two main response types (final vs brain_frame). Its main weakness is the lack of concrete examples — an example brain_frame payload, a sample proposal_text with the PREDICT line, and example acc_act call with actual parameters would significantly improve actionability. The workflow is clear but could benefit from error handling guidance.

Suggestions

Add a concrete example of a brain_frame response and the corresponding acc_act continue call with actual JSON payloads for frame_id, submit_token, and proposal_text.

Include an example of a well-formed proposal_text ending with the PREDICT line to make the format unambiguous.

Remove the duplicated description in the 'When to Use' section — it repeats the skill description verbatim and wastes tokens.

DimensionReasoningScore

Conciseness

The content is fairly lean and assumes Claude understands MCP verbs, runtime concepts, and scored-memory loops. The 'When to Use' section repeats the description almost verbatim, which is a minor redundancy, but otherwise every line carries information.

4 / 5

Actionability

The steps describe what to call and what to pass, but there are no concrete executable examples — no actual JSON payloads for the input objects, no example brain_frame structure, and no example of a well-formed proposal_text with the PREDICT line. The guidance is specific enough to follow but not copy-paste ready.

3 / 5

Workflow Clarity

The numbered steps form a clear sequence covering the main flow (call, handle final vs brain_frame, submit, close). Step 5 acts as a constraint/validation rule. However, there's no explicit error handling or feedback loop for what happens if the continue call fails or returns another frame, which is a minor gap.

4 / 5

Progressive Disclosure

This is a simple, short skill under 50 lines with a single task. The content is well-organized with a clear 'When to Use' section and numbered steps. No external references are needed given the brevity and scope.

5 / 5

Total

16

/

20

Passed

Description

3%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.

This description is nearly unintelligible, composed entirely of opaque internal jargon with no concrete actions, no natural trigger terms, and no clear indication of what the skill does or when to use it. It would be essentially impossible for Claude to correctly select this skill based on any user request phrased in natural language.

Suggestions

Rewrite the description in plain language explaining what real-world task or goal this skill accomplishes (e.g., 'Solves complex multi-step problems by breaking them into sub-goals').

Add a 'Use when...' clause with natural trigger terms that a user might actually say (e.g., 'Use when the user asks to solve a complex problem, plan a strategy, or reason through a multi-step task').

Remove or translate internal jargon like 'acc_act', 'brain_frame', and 'scored-memory loop' into user-facing language that describes observable capabilities.

DimensionReasoningScore

Specificity

The description uses entirely abstract, jargon-heavy language ('scored-memory loop', 'brain_frame', 'acc_act(runtime="solve")') without describing any concrete, understandable actions. No real-world task or capability is identifiable.

1 / 5

Completeness

Neither the 'what' nor the 'when' is meaningfully answered. The description is impenetrable jargon that fails to communicate what the skill does or when it should be selected.

1 / 5

Trigger Term Quality

No natural keywords a user would ever say are present. Terms like 'acc_act', 'brain_frame', 'scored-memory loop' are opaque internal jargon that no user would naturally use in a request.

1 / 5

Distinctiveness Conflict Risk

While the bizarre jargon is unlikely to overlap with normal skills, the description is so vague about its actual purpose that it's impossible to know what it conflicts with. It's distinctive only by being incomprehensible, not by clearly carving out a niche.

2 / 5

Total

5

/

20

Passed

Validation

100%

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

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository
administrakt0r/AI-Agents-Safe-Coding-Skills
Reviewed

Table of Contents

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