CtrlK
BlogDocsLog inGet started
Tessl Logo
SkillPublic

bedrock-agentcore-policy

Amazon Bedrock AgentCore Policy for defining agent boundaries using natural language and Cedar. Deterministic policy enforcement at the Gateway level. Use when setting agent guardrails, access control, tool permissions, or compliance rules.

Quality

75%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide
SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./skills/bedrock-agentcore-policy/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

63%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 well-structured and highly actionable for product-specific API usage, with clear operation sequences and validation checkpoints. Its weaknesses are redundancy (Cedar quick reference duplicating pattern examples, padded principles/quality-targets sections) and broken progressive disclosure: three reference files are cited but missing, leaving their content inlined in an oversized SKILL.md.

Suggestions

Create the three cited reference files (references/cedar-syntax.md, references/policy-patterns.md, references/troubleshooting.md) and move the inlined Cedar Quick Reference, the Operation 3 pattern library, and the debugging content into them, keeping SKILL.md as a concise overview with pointers.

Trim redundant or padded sections: remove the Cedar Quick Reference that duplicates Operation 3 patterns, and reframe or drop 'Key Principles (validated by AWS December 2025)' and 'Quality Targets', which add time-sensitive detail without operational value.

Make the validation example executable by defining or removing the undefined simulate_policy() helper in the test-scenario code, and add an explicit feedback loop for when policy validation reports issues (e.g., refine the natural-language description and re-run generation).

DimensionReasoningScore

Conciseness

Mostly product-specific content Claude would not already know, but it could be tightened: the Cedar Quick Reference section largely duplicates the policy patterns in Operation 3, and 'Key Principles (validated by AWS December 2025)' and 'Quality Targets' add time-sensitive padding without a deprecated/old-patterns framing. This fits 'mostly efficient but includes some unnecessary explanation or could be tightened' rather than the leaner level-4 anchor.

3 / 5

Actionability

Concrete, mostly copy-paste-ready boto3 code (start_policy_generation with waiter, create_policy, create_policy_engine, update_policy_engine) plus Cedar snippets, with minor gaps: the test-scenario example calls an undefined simulate_policy() helper and Operation 5 reuses an undefined generation_id. This matches 'mostly executable guidance; concrete code or commands with minor gaps'.

4 / 5

Workflow Clarity

Five operations each carry a purpose, time estimate, and numbered sequence, with waiter-based checkpoints (PolicyGenerationCompleted, PolicyEngineActive), validation-results review, and ALLOW/DENY test scenarios. It falls short of the top anchor because there is no explicit 'if validation fails, refine and re-run' feedback loop and the test harness is not executable as written.

4 / 5

Progressive Disclosure

The References section clearly signals one-level-deep files, but none of the three referenced files (references/cedar-syntax.md, references/policy-patterns.md, references/troubleshooting.md) exist in the bundle, and the detailed content they should hold (Cedar syntax guide, patterns library, troubleshooting) is inlined in a roughly 590-line body. This matches 'some structure but could be better organized' with content that should be separate kept inline.

3 / 5

Total

14

/

20

Passed

Description

78%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.

A strong description that clearly and explicitly states both what the skill does and when to use it, with natural trigger terms in third-person voice. Its main weaknesses are modest action coverage in the 'what' portion and a minor trigger overlap between 'agent guardrails' and Bedrock Guardrails content filtering.

DimensionReasoningScore

Specificity

The description names the domain ('Amazon Bedrock AgentCore Policy') and one to two concrete actions ('defining agent boundaries using natural language and Cedar', 'Deterministic policy enforcement at the Gateway level'), but does not enumerate the broader capability set such as generating Cedar from natural language, authoring Cedar directly, or validating policies. This matches the anchor 'Names domain and 1-2 concrete actions, but not comprehensive' rather than the level-4 anchor requiring several specific actions.

3 / 5

Completeness

It explicitly answers what ('defining agent boundaries using natural language and Cedar. Deterministic policy enforcement at the Gateway level') and when ('Use when setting agent guardrails, access control, tool permissions, or compliance rules') with concrete trigger phrases, in third-person voice, matching the top anchor.

5 / 5

Trigger Term Quality

'Use when setting agent guardrails, access control, tool permissions, or compliance rules' provides good natural keyword coverage a user would actually say. Missing common variations such as 'RBAC', 'role-based access control', or 'deny rules', so it falls just short of the comprehensive-synonym anchor.

4 / 5

Distinctiveness Conflict Risk

The named product (Bedrock AgentCore, Cedar, Gateway) is a clear niche with distinct triggers, but the trigger term 'agent guardrails' overlaps with Bedrock Guardrails content-filtering requests, which the skill itself explicitly excludes. Mostly distinct with minor overlap risk, matching the level-4 anchor.

4 / 5

Total

16

/

20

Passed

Validation

81%

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

Validation — 13 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (595 lines); consider splitting into references/ and linking

Warning

allowed_tools_field

'allowed-tools' contains unusual tool name(s)

Warning

referenced_paths_exist

Referenced path issues: 3 missing

Warning

Total

13

/

16

Passed

Repository

fernandezbaptiste/Skrillz

Path

skills/bedrock-agentcore-policy/SKILL.md

Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.