REPOGEO REPORT · LITE

Opencode-DCP/opencode-dynamic-context-pruning

Default branch master · commit 74f90495 · scanned 6/24/2026, 10:12:49 PM

GitHub: 3,493 stars · 191 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE

22 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

1 pass · 1 warn · 0 fail

Objective metadata checks

AI knows your name

1 / 3

Direct prompts that named your repo

HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface Opencode-DCP/opencode-dynamic-context-pruning, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION

mediumreadme#1

Add a 'Key Features for OpenCode Users' section to the README

Why:

COPY-PASTE FIX

## Key Features for OpenCode Users

- **Automatic Token Optimization:** Intelligently prunes conversation context to reduce token usage within OpenCode.
- **High-Fidelity Summaries:** Replaces stale content with technical summaries, preserving crucial information.
- **Seamless OpenCode Integration:** Designed specifically as a plugin for OpenCode, integrating directly into your workflow.
- **Session History Preservation:** Prunes content with placeholders, ensuring your original session history remains unmodified.

lowhomepage#2
Add a homepage URL to the repository metadata
Why:
COPY-PASTE FIX
```
https://www.npmjs.com/package/@tarquinen/opencode-dcp
```

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall

0 / 2

0% of queries surface Opencode-DCP/opencode-dynamic-context-pruning

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

langchain-ai/langchain

Recommended in 3 of 2 queries

COMPETITOR LEADERBOARD

langchain-ai/langchain · recommended 3×
run-llama/llama_index · recommended 2×
GPT-3.5 Turbo / GPT-4 · recommended 1×
Pinecone · recommended 1×
weaviate/weaviate · recommended 1×

CATEGORY QUERY
How to reduce token consumption and manage conversation history in AI assistant interactions?
you: not recommended
AI recommended (in order):
1. GPT-3.5 Turbo / GPT-4
2. LangChain's ConversationSummaryBufferMemory (langchain-ai/langchain)
3. LlamaIndex's ChatEngine with Contextual Compression (run-llama/llama_index)
4. LangChain's ConversationBufferWindowMemory (langchain-ai/langchain)
5. LlamaIndex (run-llama/llama_index)
6. LangChain's VectorStoreRetrieverMemory (langchain-ai/langchain)
7. Pinecone
8. Weaviate (weaviate/weaviate)
9. ChromaDB (chroma-core/chroma)
10. PostgreSQL
11. MongoDB
12. Redis
AI recommended 12 alternatives but never named Opencode-DCP/opencode-dynamic-context-pruning. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What are the best tools for intelligently pruning LLM conversation context to save costs?
you: not recommended
AI recommended (in order):
1. LangChain
2. LlamaIndex
3. Haystack
4. OpenAI API
5. Microsoft Semantic Kernel
6. Guidance
AI recommended 6 alternatives but never named Opencode-DCP/opencode-dynamic-context-pruning. This is the gap to close.
Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

Metadata completeness
warn
Suggestion:
README presence
pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

Compared to common alternatives in this category, what is the core differentiator of Opencode-DCP/opencode-dynamic-context-pruning?
pass
AI did not name Opencode-DCP/opencode-dynamic-context-pruning — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts Opencode-DCP/opencode-dynamic-context-pruning in production, what risks or prerequisites should they evaluate first?
pass
AI named Opencode-DCP/opencode-dynamic-context-pruning explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
In one sentence, what problem does the repo Opencode-DCP/opencode-dynamic-context-pruning solve, and who is the primary audience?
pass
AI did not name Opencode-DCP/opencode-dynamic-context-pruning — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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MARKDOWN (README)

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Opencode-DCP/opencode-dynamic-context-pruning — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite