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trellis-session-insight

Reach into past AI conversation history through the `trellis mem` CLI. Use whenever the user asks 'how did we solve X last time', 'have we discussed this before', 'what was the decision on X', 'remind me what we did in this task', '上次怎么解的', '之前讨论过吗', '想起一段对话', or when starting a brainstorm that overlaps prior work, debugging a familiar bug, continuing a task across sessions, or doing a finish-work review. Returns raw past dialogue; decide for the moment whether to update spec, append to task notes, quote inline in the answer, or just internalize.

Quality

90%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

The canonical home for this skill is trellis-session-insight in EcoPasteHub/EcoPaste

SKILL.md
Quality
Evals
Security

Quality

Content

86%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 capability skill: executable commands with concrete output-destination guidance, clean one-level-deep reference files, and a sharp when/when-not-to-use framing. The only deductions are minor philosophical padding and an operating sequence that must be assembled from multiple sections rather than read as one flow.

Suggestions

Trim the meta-commentary sentences ('It is a tool, not a ceremony', 'Forcing every recall into a fixed file makes the file grow into noise') to their operative guidance.

Add a short ordered recall flow (e.g., 1. search/list → 2. context/extract → 3. choose destination) so the multi-subcommand workflow reads as a sequence instead of parallel sections.

DimensionReasoningScore

Conciseness

The body is dense and assumes Claude's competence (no explaining what session logs or CLIs are), but carries minor trimmable padding — e.g., 'It is a tool, not a ceremony', 'Forcing every recall into a fixed file makes the file grow into noise', and 'keep that handy when training instinct'. These are philosophical justifications rather than instructions, matching the 'efficient; minor instances of over-explanation' anchor rather than the every-token-earns-its-place anchor.

4 / 5

Actionability

Copy-paste-ready bash covering all 80% cases with flags and their semantics ('trellis mem search "<keyword>"', 'trellis mem extract <session-id> --phase brainstorm', 'trellis mem list --cwd <project-path>'), plus a concrete decision list for what to do with results. This matches the fully-executable top anchor.

5 / 5

Workflow Clarity

Read-only capability skill, so the destructive/batch cap does not apply, and sections are clearly organized (when / when not / what to do with output / how to call). However, the operating sequence (projects or list → search → context/extract → decide destination) is distributed across sections with only one explicit sequencing hint ('When you do not know the session id yet, start with list + filter'), fitting the 'clear sequence with minor gaps' anchor rather than anchor 5's explicit end-to-end flow.

4 / 5

Progressive Disclosure

The body keeps only the 80% cases inline and cleanly splits the full flag reference to references/cli-quick-reference.md and verbatim trigger phrasings to references/triggering-patterns.md. Both files exist, are one level deep, and are clearly signaled with their content described — matching the 'clear overview with well-signaled one-level-deep references' anchor.

5 / 5

Total

18

/

20

Passed

Description

90%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 excellent bilingual verbatim triggers and an explicit 'Use whenever' clause covering both what and when. The only weakness is that the capability is described at a high level ('reach into', 'returns') rather than enumerating the concrete subcommands the CLI offers.

Suggestions

Enumerate one or two concrete subcommands in the description (e.g., 'search and extract past dialogue') to lift specificity from domain-plus-tool to named actions.

Mention the supported platforms (Claude Code / Codex / Pi session logs) briefly so the description scopes what history is reachable.

DimensionReasoningScore

Specificity

The description names the domain ('past AI conversation history') and the concrete mechanism ('the `trellis mem` CLI' that 'Returns raw past dialogue'), but stops at 1-2 actions — subcommands like search/extract/context are not listed. This matches the 'Names domain and 1-2 concrete actions' anchor; it is below anchor 4, which requires several specific actions.

3 / 5

Completeness

It explicitly answers both what ('Reach into past AI conversation history through the `trellis mem` CLI... Returns raw past dialogue') and when ('Use whenever the user asks...' with concrete trigger phrases). This matches the anchor for clearly and explicitly answering both with concrete triggers.

5 / 5

Trigger Term Quality

Verbatim natural phrases in two languages ('how did we solve X last time', 'have we discussed this before', 'what was the decision on X', '上次怎么解的', '之前讨论过吗') plus situational triggers (familiar-bug debugging, cross-session continuation, finish-work review). Coverage including synonyms is comprehensive, matching the top anchor.

5 / 5

Distinctiveness Conflict Risk

A clear niche — recalling past AI conversation history via a named CLI — with distinct triggers anchored to recall intent. Situational phrases like 'starting a brainstorm that overlaps prior work' are mildly broad but the recall scope keeps conflict risk minimal, fitting the 'clear niche with distinct triggers' anchor over the anchor 4 example.

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

EcoPasteHub/EcoPaste

Path

.kiro/skills/trellis-session-insight/SKILL.md

Reviewed

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