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agently-migration

Use when migrating an existing LangChain, LangGraph, LlamaIndex, or CrewAI system into Agently and mapping each source behavior to its actual request, runtime, context/storage, or TriggerFlow owner.

Quality

86%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

78%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.

A well-structured, dense migration guide: a clear behavior-to-owner decision table, a sequenced five-step method with an explicit evidence-comparison checkpoint, and one-level-deep references that all resolve to real, substantive mapping files. The main weaknesses are the convoluted version-check preamble that inflates the token budget and implied-rather-than-explicit retry loops after validation.

Suggestions

Move the read-only version-check procedure into a reference file (or trim it to a few lines), keeping the SKILL.md body focused on the migration method — this would lift conciseness.

Make the validation feedback loop explicit in Migration Method step 4 (e.g., 'if traces or failure semantics diverge, fix the mapping and re-compare before proceeding') rather than implied by 'before broad replacement'.

Specify what representative before/after evidence looks like (a trace snippet, a state-transition listing) so step 4's comparison is directly executable.

DimensionReasoningScore

Conciseness

The owner-map table, migration method, and cautions are dense with no explanation of concepts Claude already knows. Not a 5 because the "First use: read-only version check" section (~a third of the body, e.g. "Equal means the recorded source matches, not that local supplements are absent") is convoluted and tangential to the migration task, and could be tightened. Not a 3 because nothing there is concept padding — it is operational constraint language, and the rest is lean.

4 / 5

Actionability

The owner map is a concrete decision table ("One model call, prompt contract, structured result... → agently-request / ModelRequest"), and the method gives executable steps like "Migrate one representative vertical slice" with an explicit inventory checklist in step 1. Per the rubric's code-vs-instruction note, absent code is not penalized. Not a 5 because how to compare traces or format the before/after evidence is left unspecified.

4 / 5

Workflow Clarity

The five-step Migration Method is clearly sequenced with a validation checkpoint ("Compare source and target traces, final artifacts, state transitions, interruption/recovery behavior, and failure semantics before broad replacement") and a gating condition before broad replacement, so the destructive/batch cap at 3 does not apply. Not a 5 because the fix-and-recompare feedback loop is only implied, never stated as an explicit retry step.

4 / 5

Progressive Disclosure

Verified against the actual bundle: all four referenced files (references/langchain-to-agently.md, langgraph-to-triggerflow.md, llamaindex-to-agently.md, crewai-to-agently.md) exist, are substantive (79-90 lines), one level deep, and clearly routed by topic ("LangChain agents, models, prompts... → langchain-to-agently.md"). The overview (owner map, method, cautions) is appropriately kept in SKILL.md while per-framework detail is split out — clean navigation matching the top anchor.

5 / 5

Total

17

/

20

Passed

Description

87%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 with an explicit 'Use when' trigger naming all four source frameworks, paired with a concrete statement of what the skill does (behavior-to-owner mapping). Framework names provide excellent natural triggers; only minor synonym coverage and capability breadth are missing.

DimensionReasoningScore

Specificity

"migrating an existing LangChain, LangGraph, LlamaIndex, or CrewAI system into Agently and mapping each source behavior to its actual request, runtime, context/storage, or TriggerFlow owner" names the four source frameworks and the four concrete Agently owner targets. Not a 5 because it covers two actions (migrate, map) while the skill's body also covers evidence-preserved verification, which the description omits; not a 3 because the named owners and frameworks go well beyond 1-2 generic actions.

4 / 5

Completeness

Explicitly answers both: what — "mapping each source behavior to its actual request, runtime, context/storage, or TriggerFlow owner" — and when — "Use when migrating an existing LangChain, LangGraph, LlamaIndex, or CrewAI system into Agently", with concrete framework-name trigger phrases. Both halves are explicit and concrete, matching the top anchor.

5 / 5

Trigger Term Quality

"LangChain", "LangGraph", "LlamaIndex", "CrewAI", "Agently", and "migrating" are exactly the natural terms a user would say when they need this skill. Not a 5 because common synonyms like "port", "rewrite", or "convert to Agently" are absent, leaving a few natural trigger phrasings uncovered.

4 / 5

Distinctiveness Conflict Risk

The niche is unambiguous: migration from four named frameworks into Agently. No generic-skill overlap; these triggers would almost never fire for the wrong skill. Matches the clear-niche/minimal-conflict anchor.

5 / 5

Total

18

/

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.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

AgentEra/Agently-Skills

Path

skills/agently-migration/SKILL.md

Reviewed

Table of Contents

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